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Awesome Knowledge Distillation in Computer vision

[TOC]

Diffusion Knowledge Distillation

Title Venue Note
A Comprehensive Survey on Knowledge Distillation of Diffusion Models 2023 Weijian Luo. [pdf]
Knowledge distillation in iterative generative models for improved sampling speed 2021 Eric Luhman, Troy Luhman. [pdf]
Progressive Distillation for Fast Sampling of Diffusion Models ICLR 2022 Tim Salimans and Jonathan Ho. [pdf]
On Distillation of Guided Diffusion Models CVPR 2023 Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans. [pdf]
TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation 2023 Berthelot, David, Autef, Arnaud, Lin, Jierui, Yap, Dian Ang, Zhai, Shuangfei, Hu, Siyuan, Zheng, Daniel, Talbott, Walter, Gu, Eric. [pdf]
BK-SDM: Architecturally Compressed Stable Diffusion for Efficient Text-to-Image Generation ICML 2023 Kim, Bo-Kyeong, Song, Hyoung-Kyu, Castells, Thibault, Choi, Shinkook. [pdf]
On Architectural Compression of Text-to-Image Diffusion Models 2023 Kim, Bo-Kyeong, Song, Hyoung-Kyu, Castells, Thibault, Choi, Shinkook. [pdf]
Knowledge Diffusion for Distillation 2023 Tao Huang, Yuan Zhang, Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Chang Xu. [pdf]
SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds 2023 Yanyu Li, Huan Wang, Qing Jin, Ju Hu, Pavlo Chemerys, Yun Fu, Yanzhi Wang, Sergey Tulyakov, Jian Ren1. [pdf]
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping 2023 Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Josh Susskind. [pdf]
Consistency models 2023 Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever. [pdf]

Knowledge Distillation for Semantic Segmentation

Title Venue Note
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks arXiv:1709.00513
Knowledge Distillation for Semantic Segmentation
Structured knowledge distillation for semantic segmentation CVPR-2019
Intra-class feature variation distillation for semantic segmentation ECCV-2020
Channel-wise knowledge distillation for dense prediction ICCV-2021
Double Similarity Distillation for Semantic Image Segmentation TIP-2021
Cross-Image Relational Knowledge Distillation for Semantic Segmentation CVPR-2022

Knowledge Distillation for Object Detection

Title Venue Note
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks arXiv:1709.00513
Mimicking very efficient network for object detection CVPR 2017 pdf
Distilling object detectors with fine-grained feature imitation CVPR 2019 pdf
General instance distillation for object detection CVPR 2021 pdf
Distilling object detectors via decoupled features CVPR 2021 pdf
Distilling object detectors with feature richness NeurIPS 2021 pdf
Focal and global knowledge distillation for detectors CVPR 2022 pdf
Rank Mimicking and Prediction-guided Feature Imitation AAAI 2022 pdf
Prediction-Guided Distillation ECCV 2022 pdf
Masked Distillation with Receptive Tokens ICLR 2023 pdf
Structural Knowledge Distillation for Object Detection NeurIPS 2022 OpenReview
Dual Relation Knowledge Distillation for Object Detection IJCAI 2023 pdf
GLAMD: Global and Local Attention Mask Distillation for Object Detectors ECCV 2022 ECVA
G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation ICCV 2021 CVF
PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficient NeurIPS 2022 OpenReview
MimicDet: Bridging the Gap Between One-Stage and Two-Stage Object Detection ECCV 2020 ECVA
LabelEnc: A New Intermediate Supervision Method for Object Detection ECCV 2020 ECVA
Title Venue Note
HEtero-Assists Distillation for Heterogeneous Object Detectors ECCV 2022 HEAD
LGD: Label-Guided Self-Distillation for Object Detection AAAI 2022 LGD
When Object Detection Meets Knowledge Distillation: A Survey TPAMI
ScaleKD: Distilling Scale-Aware Knowledge in Small Object Detector CVPR 2023 ScaleKD
CrossKD: Cross-Head Knowledge Distillation for Dense Object Detection arXiv:2306.11369 CrossKD

Knowledge Distillation in Vision Transformers

Title Venue Note
Training data-efficient image transformers & distillation through attention ICML2021
Co-advise: Cross inductive bias distillation CVPR2022
Tinyvit: Fast pretraining distillation for small vision transformers arXiv:2207.10666
Attention Probe: Vision Transformer Distillation in the Wild ICASSP2022
Dear KD: Data-Efficient Early Knowledge Distillation for Vision Transformers CVPR2022
Efficient vision transformers via fine-grained manifold distillation NIPS2022
Cross-Architecture Knowledge Distillation arXiv:2207.05273
MiniViT: Compressing Vision Transformers with Weight Multiplexing CVPR2022
ViTKD: Practical Guidelines for ViT feature knowledge distillation arXiv 2022 code

Knowledge Distillation for Teacher-Student Gaps

Title Venue Note
Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher AAAI2020
Search to Distill: Pearls are Everywhere but not the Eyes CVPR 2020
Reducing the Teacher-Student Gap via Spherical Knowledge Disitllation arXiv:2020
Knowledge Distillation via the Target-aware Transformer CVPR2022
Decoupled Knowledge Distillation CVPR 2022 code
Prune Your Model Before Distill It ECCV 2022 code
Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again NeurIPS 2022
Weighted Distillation with Unlabeled Examples NeurIPS 2022
Respecting Transfer Gap in Knowledge Distillation NeurIPS 2022
Knowledge Distillation from A Stronger Teacher arXiv:2205.10536
Masked Generative Distillation ECCV 2022 code
Curriculum Temperature for Knowledge Distillation AAAI 2023 code
Knowledge distillation: A good teacher is patient and consistent CVPR 2022
Knowledge Distillation with the Reused Teacher Classifier CVPR 2022
Scaffolding a Student to Instill Knowledge ICLR2023
Function-Consistent Feature Distillation ICLR2023
Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation ICLR2023
Supervision Complexity and its Role in Knowledge Distillation ICLR2023

Logits Knowledge Distillation

Title Venue Note
Distilling the knowledge in a neural network arXiv:1503.2531
Deep Model Compression: Distilling Knowledge from Noisy Teachers arXiv:161009650
Semi-Supervised Knowledge Transfer for Deep Learning from Private Training Data ICLR 2017
Knowledge Adaptation: Teaching to Adapt Arxiv:17022052
Learning from Multiple Teacher Networks KDD 2017
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results NIPS 2017
Training Deep Neural Networks in Generations:A More Tolerant Teacher Educates Better Students arXiv:1805.551
Moonshine:Distilling with Cheap Convolutions NIPS 2018
Learning from Multiple Teacher Networks KDD 2017
Positive-Unlabeled Compression on the Cloud NIPS 2019
Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework arXiv:1910.12061
Preparing Lessons: Improve Knowledge Distillation with Better Supervision arXiv:1911.7471
Adaptive Regularization of Labels arXiv:1908.5474
Learning Metrics from Teachers: Compact Networks for Image Embedding CVPR 2019
Diversity with Cooperation: Ensemble Methods for Few-Shot Classification ICCV 2019
Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher arXiv:1902.3393
MEAL: Multi-Model Ensemble via Adversarial Learning AAAI 2019
Revisit Knowledge Distillation: a Teacher-free Framework CVPR 2020 [code]
Ensemble Distribution Distillation ICLR 2020
Noisy Collaboration in Knowledge Distillation ICLR 2020
Self-training with Noisy Student improves ImageNet classification CVPR 2020
QUEST: Quantized embedding space for transferring knowledge CVPR 2020(pre)
Meta Pseudo Labels ICML 2020
Subclass Distillation ICML2020
Boosting Self-Supervised Learning via Knowledge Transfer CVPR 2018
Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation from a Blackbox Model CVPR 2020 [code]
Regularizing Class-wise Predictions via Self-knowledge Distillation CVPR 2020 [code]
Rethinking Data Augmentation: Self-Supervision and Self-Distillation ICLR 2020
What it Thinks is Important is Important: Robustness Transfers through Input Gradients CVPR 2020
Role-Wise Data Augmentation for Knowledge Distillation ICLR 2020 [code]
Distilling Effective Supervision from Severe Label Noise CVPR 2020
Learning with Noisy Class Labels for Instance Segmentation ECCV 2020
Self-Distillation Amplifies Regularization in Hilbert Space arXiv:2002.5715
MINILM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers arXiv:200210957
Hydra: Preserving Ensemble Diversity for Model Distillation arXiv:20014694
Teacher-Class Network: A Neural Network Compression Mechanism arXiv:2004.3281
Learning from a Lightweight Teacher for Efficient Knowledge Distillation arXiv:2005.9163
Self-Distillation as Instance-Specific Label Smoothing arXiv:2006.5065
Self-supervised Knowledge Distillation for Few-shot Learning arXiv:2006.09785
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation arXiv:2007.1951
Few Sample Knowledge Distillation for Efficient Network Compression CVPR 2020
Learning What and Where to Transfer ICML 2019
Transferring Knowledge across Learning Processes ICLR 2019
Semantic-Aware Knowledge Preservation for Zero-Shot Sketch-Based Image Retrieval ICCV 2019
Diversity with Cooperation: Ensemble Methods for Few-Shot Classification ICCV 2019
Knowledge Representing: Efficient, Sparse Representation of Prior Knowledge for Knowledge Distillation arXiv:191105329v1
Progressive Knowledge Distillation For Generative Modeling ICLR 2020
Few Shot Network Compression via Cross Distillation AAAI 2020

Intermediate Knowledge Distillation

Title Venue Note
Fitnets: Hints for thin deep nets arXiv:1412.6550
Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer ICLR 2017
Knowledge Projection for Effective Design of Thinner and Faster Deep Neural Networks arXiv:1710.9505
A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning CVPR 2017
Paraphrasing complex network: Network compression via factor transfer NIPS 2018
Knowledge transfer with jacobian matching ICML 2018
Like What You Like: Knowledge Distill via Neuron Selectivity Transfer CVPR2018
An Embarrassingly Simple Approach for Knowledge Distillation MLR 2018
Self-supervised knowledge distillation using singular value decomposition ECCV 2018
Learning Deep Representations with Probabilistic Knowledge Transfer ECCV 2018
Correlation Congruence for Knowledge Distillation ICCV 2019
Similarity-Preserving Knowledge Distillation ICCV 2019
Variational Information Distillation for Knowledge Transfer CVPR 2019
Knowledge Distillation via Instance Relationship Graph CVPR 2019
Knowledge Distillation via Instance Relationship Graph CVPR 2019
Knowledge Distillation via Route Constrained Optimization ICCV 2019
Similarity-Preserving Knowledge Distillation ICCV 2019
Stagewise Knowledge Distillation arXiv: 1911.6786
Distilling Object Detectors with Fine-grained Feature Imitation ICLR 2020
Knowledge Squeezed Adversarial Network Compression AAAI 2020
Knowledge Distillation from Internal Representations AAAI 2020
Knowledge Flow:Improve Upon Your Teachers ICLR 2019
LIT: Learned Intermediate Representation Training for Model Compression ICML 2019
A Comprehensive Overhaul of Feature Distillation ICCV 2019
Residual Knowledge Distillation arXiv:2002.9168
Knowledge distillation via adaptive instance normalization arXiv:2003.4289
Channel Distillation: Channel-Wise Attention for Knowledge Distillation arXiv:2006.01683
Matching Guided Distillation ECCV 2020
Differentiable Feature Aggregation Search for Knowledge Distillation ECCV 2020
Local Correlation Consistency for Knowledge Distillation ECCV 2020

Oneline Knowledge Distillation

Title Venue Note
Deep Mutual Learning CVPR 2018
Born-Again Neural Networks ICML 2018
Knowledge distillation by on-the-fly native ensemble NIPS 2018
Collaborative learning for deep neural networks NIPS 2018
Unifying Heterogeneous Classifiers with Distillation CVPR 2019
Snapshot Distillation: Teacher-Student Optimization in One Generation CVPR 2019
Deeply-supervised knowledge synergy CVPR 2019
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation ICCV 2019
Distillation-Based Training for Multi-Exit Architectures ICCV 2019
MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks arXiv:1911.9418
FEED: Feature-level Ensemble for Knowledge Distillation AAAI 2020
Stochasticity and Skip Connection Improve Knowledge Transfer ICLR 2020
Online Knowledge Distillation with Diverse Peers AAAI 2020
Online Knowledge Distillation via Collaborative Learning CVPR 2020
Collaborative Learning for Faster StyleGAN Embedding arXiv:20071758
Online Knowledge Distillation via Collaborative Learning CVPR 2020
Feature-map-level Online Adversarial Knowledge Distillation ICML 2020
Knowledge Transfer via Dense Cross-layer Mutual-distillation ECCV 2020
MetaDistiller: Network Self-boosting via Meta-learned Top-down Distillation ECCV 2020
ResKD: Residual-Guided Knowledge Distillation arXiv:2006.4719
Interactive Knowledge Distillation arXiv:2007.1476

Understanding Knowledge Distillation

Title Venue Note
Do deep nets really need to be deep? NIPS 2014
When Does Label Smoothing Help? NIPS 2019
Towards Understanding Knowledge Distillation AAAI 2019
Harnessing deep neural networks with logical rules ACL 2016
Adaptive Regularization of Labels arXiv:1908
Knowledge Isomorphism between Neural Networks arXiv:1908
Understanding and Improving Knowledge Distillation arXiv:2002.3532
The State of Knowledge Distillation for Classification arXiv:1912.10850
Explaining Knowledge Distillation by Quantifying the Knowledge CVPR 2020
DeepVID: deep visual interpretation and diagnosis for image classifiers via knowledge distillation IEEE Trans, 2019
On the Unreasonable Effectiveness of Knowledge Distillation: Analysis in the Kernel Regime arXiv:2003.13438
Why distillation helps: a statistical perspective arXiv:2005.10419
Transferring Inductive Biases through Knowledge Distillation arXiv:2006.555
Does label smoothing mitigate label noise? Lukasik, Michal et al ICML 2020
An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation arXiv:2006.3810
Does Adversarial Transferability Indicate Knowledge Transferability? arXiv:2006.14512
On the Demystification of Knowledge Distillation: A Residual Network Perspective arXiv:2006.16589
Teaching To Teach By Structured Dark Knowledge ICLR 2020
Inter-Region Affinity Distillation for Road Marking Segmentation CVPR 2020 [code]
Heterogeneous Knowledge Distillation using Information Flow Modeling CVPR 2020 [code]
Local Correlation Consistency for Knowledge Distillation ECCV2020
Few-Shot Class-Incremental Learning CVPR 2020
Unifying distillation and privileged information ICLR 2016

Knowledge Distillation with Pruning , Quantization, NAS

Title Venue Note
Accelerating Convolutional Neural Networks with Dominant Convolutional Kernel and Knowledge Pre-regression ECCV 2016
N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning ICLR 2018
Slimmable Neural Networks ICLR 2018
Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy NIPS 2018
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning ICCV 2019
LightPAFF: A Two-Stage Distillation Framework for Pre-training and Fine-tuning ICLR 2020
Pruning with hints: an efficient framework for model acceleration ICLR 2020
Knapsack Pruning with Inner Distillation arXiv:2002.8258
Training convolutional neural networks with cheap convolutions and online distillation arXiv:190913063
Cooperative Pruning in Cross-Domain Deep Neural Network Compression IJCAI 2019
QKD: Quantization-aware Knowledge Distillation arXiv:191112491v1
Neural Network Pruning with Residual-Connections and Limited-Data CVPR 2020
Training Quantized Neural Networks with a Full-precision Auxiliary Module CVPR 2020
Towards Effective Low-bitwidth Convolutional Neural Networks CVPR 2018
Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations arXiv:19084680
Paying more attention to snapshots of Iterative Pruning: Improving Model Compression via Ensemble Distillation arXiv:200611487
Knowledge Distillation Beyond Model Compression arxiv:20071493
Teacher Guided Architecture Search ICCV 2019
Distillation Guided Residual Learning for Binary Convolutional Neural Networks ECCV 2020
MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution ECCV 2020
Improving Neural Architecture Search Image Classifiers via Ensemble Learning arXiv:19036236
Blockwisely Supervised Neural Architecture Search with Knowledge Distillation arXiv:191113053v1
Towards Oracle Knowledge Distillation with Neural Architecture Search AAAI 2020
Search for Better Students to Learn Distilled Knowledge arXiv:200111612
Circumventing Outliers of AutoAugment with Knowledge Distillation arXiv:200311342
Network Pruning via Transformable Architecture Search NIPS 2019
Search to Distill: Pearls are Everywhere but not the Eyes CVPR 2020
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks ICML 2020 [code]

Application of Knowledge Distillation

Sub Title Venue
Graph Graph-based Knowledge Distillation by Multi-head Attention Network arXiv:19072226
Graph Representation Learning via Multi-task Knowledge Distillation arXiv:19115700
Deep geometric knowledge distillation with graphs arXiv:19113080
Better and faster: Knowledge transfer from multiple self-supervised learning tasks via graph distillation for video classification IJCAI 2018
Distillating Knowledge from Graph Convolutional Networks CVPR 2020
Face Face model compression by distilling knowledge from neurons AAAI 2016
MarginDistillation: distillation for margin-based softmax arXiv:2003.2586
ReID Distilled Person Re-Identification: Towards a More Scalable System CVPR 2019
Robust Re-Identification by Multiple Views Knowledge Distillation ECCV 2020 [code]
Detection Learning efficient object detection models with knowledge distillation NIPS 2017
Distilling Object Detectors with Fine-grained Feature Imitation CVPR 2019
Relation Distillation Networks for Video Object Detection ICCV 2019
Learning Lightweight Face Detector with Knowledge Distillation IEEE 2019
Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection ICCV 2019
Learning Lightweight Lane Detection CNNs by Self Attention Distillation ICCV 2019
A Multi-Task Mean Teacher for Semi-Supervised Shadow Detection CVPR 2020 [code]
Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer ECCV 2020
A Multi-Task Mean Teacher for Semi-Supervised Shadow Detection CVPR 2020 [code]
Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection IEEE 2020 [code]
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings CVPR 2020
Distilling Knowledge from Refinement in Multiple Instance Detection Networks arXiv:2004.10943
Enabling Incremental Knowledge Transfer for Object Detection at the Edge arXiv:2004.5746
Pose DOPE: Distillation Of Part Experts for whole-body 3D pose estimation in the wild ECCV 2020
Fast Human Pose Estimation CVPR 2019
Distill Knowledge From NRSfM for Weakly Supervised 3D Pose Learning ICCV 2019
Segmentation ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes CVPR 2018
Knowledge Distillation for Incremental Learning in Semantic Segmentation arXiv:1911.3462
Geometry-Aware Distillation for Indoor Semantic Segmentation CVPR 2019
Structured Knowledge Distillation for Semantic Segmentation CVPR 2019
Self-similarity Student for Partial Label Histopathology Image Segmentation ECCV 2020
Knowledge Distillation for Brain Tumor Segmentation arXiv:2002.3688
ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes CVPR 2018
Low-Vision Lightweight Image Super-Resolution with Information Multi-distillation Network ICCVW 2019
Collaborative Distillation for Ultra-Resolution Universal Style Transfer CVPR 2020 [code]
Video Efficient Video Classification Using Fewer Frames CVPR 2019
Relation Distillation Networks for Video Object Detection ICCV 2019
Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection ICCV 2019
Progressive Teacher-student Learning for Early Action Prediction CVPR 2019
MOD: A Deep Mixture Model with Online Knowledge Distillation for Large Scale Video Temporal Concept Localization arXiv:1910.12295
AWSD:Adaptive Weighted Spatiotemporal Distillation for Video Representation ICCV 2019
Dynamic Kernel Distillation for Efficient Pose Estimation in Videos ICCV 2019
Online Model Distillation for Efficient Video Inference ICCV 2019
Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer ECCV 2020
Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition ECCV 2020
Object Relational Graph with Teacher-Recommended Learning for Video Captioning CVPR 2020
Spatio-Temporal Graph for Video Captioning with Knowledge distillation CVPR 2020 [code]
TA-Student VQA: Multi-Agents Training by Self-Questioning CVPR 2020

Data-free Knowledge Distillation

Title Venue Note
Data-Free Knowledge Distillation for Deep Neural Networks NIPS 2017
Zero-Shot Knowledge Distillation in Deep Networks ICML 2019
DAFL:Data-Free Learning of Student Networks ICCV 2019
Zero-shot Knowledge Transfer via Adversarial Belief Matching NIPS 2019
Dream Distillation: A Data-Independent Model Compression Framework ICML 2019
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion CVPR 2020
Data-Free Adversarial Distillation CVPR 2020
The Knowledge Within: Methods for Data-Free Model Compression CVPR 2020
Knowledge Extraction with No Observable Data NIPS 2019
Data-Free Knowledge Amalgamation via Group-Stack Dual-GAN CVPR 2020
DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier arXiv:1912.11960
Generative Low-bitwidth Data Free Quantization arXiv:2003.3603
This dataset does not exist: training models from generated images arXiv:1911.2888
MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation arXiv:2005.3161
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data ECCV 2020
Billion-scale semi-supervised learning for image classification arXiv:1905.00546
Data-free Parameter Pruning for Deep Neural Networks arXiv:1507.6149
Data-Free Quantization Through Weight Equalization and Bias Correction ICCV 2019
DAC: Data-free Automatic Acceleration of Convolutional Networks WACV 2019

Cross-modal Knowledge Distillation

Title Venue Note
SoundNet: Learning Sound Representations from Unlabeled Video SoundNet Architecture ECCV 2016
Cross Modal Distillation for Supervision Transfer CVPR 2016
Emotion recognition in speech using cross-modal transfer in the wild ACM MM 2018
Through-Wall Human Pose Estimation Using Radio Signals CVPR 2018
Compact Trilinear Interaction for Visual Question Answering ICCV 2019
Cross-Modal Knowledge Distillation for Action Recognition ICIP 2019
Learning to Map Nearly Anything arXiv:1909.6928
Semantic-Aware Knowledge Preservation for Zero-Shot Sketch-Based Image Retrieval ICCV 2019
UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation ICCV 2019
CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency CVPR 2019
XD:Cross lingual Knowledge Distillation for Polyglot Sentence Embeddings
Effective Domain Knowledge Transfer with Soft Fine-tuning arXiv:1909.2236
ASR is all you need: cross-modal distillation for lip reading arXiv:1911.12747
Knowledge distillation for semi-supervised domain adaptation arXiv:1908.7355
Domain Adaptation via Teacher-Student Learning for End-to-End Speech Recognition arXiv:2001.1798
Cluster Alignment with a Teacher for Unsupervised Domain Adaptation ICCV 2019.
Attention Bridging Network for Knowledge Transfer ICCV 2019
Unpaired Multi-modal Segmentation via Knowledge Distillation arXiv:2001.3111
Multi-source Distilling Domain Adaptation arXiv:1911.11554
Creating Something from Nothing: Unsupervised Knowledge Distillation for Cross-Modal Hashing CVPR 2020
Improving Semantic Segmentation via Self-Training arXiv:2004.14960
Speech to Text Adaptation: Towards an Efficient Cross-Modal Distillation arXiv:2005.8213
Joint Progressive Knowledge Distillation and Unsupervised Domain Adaptation arXiv:2005.7839
Knowledge as Priors: Cross-Modal Knowledge Generalization for Datasets without Superior Knowledge CVPR 2020
Large-Scale Domain Adaptation via Teacher-Student Learning arXiv:1708.5466
Large Scale Audiovisual Learning of Sounds with Weakly Labeled Data IJCAI 2020
Distilling Cross-Task Knowledge via Relationship Matching CVPR 2020 [code]
Modality distillation with multiple stream networks for action recognition ECCV 2018
Domain Adaptation through Task Distillation ECCV 2020

Adversarial Knowledge Distillation

Title Venue Note
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks arXiv:1709.00513
KTAN: Knowledge Transfer Adversarial Network arXiv:1810.08126
KDGAN:Knowledge Distillation with Generative Adversarial Networks. NIPS 2018
Adversarial Learning of Portable Student Networks AAAI 2018
Adversarial Network Compression ECCV 2018
Cross-Modality Distillation: A case for Conditional Generative Adversarial Networks ICASSP 2018
Adversarial Distillation for Efficient Recommendation with External Knowledge TOIS 2018
Training student networks for acceleration with conditional adversarial networks BMVC 2018
Adversarial network compression ECCV 2018
KDGAN:Knowledge Distillation with Generative Adversarial Networks NIPS 2018
DAFL:Data-Free Learning of Student Networks ICCV 2019
MEAL: Multi-Model Ensemble via Adversarial Learning AAAI 2019
Exploiting the Ground-Truth: An Adversarial Imitation Based Knowledge Distillation Approach for Event Detection AAAI 2019
Adversarially Robust Distillation AAAI 2020
GAN-Knowledge Distillation for one-stage Object Detection arXiv:1906.08467
Lifelong GAN: Continual Learning for Conditional Image Generation arXiv:1908.03884
Compressing GANs using Knowledge Distillation arXiv:1902.00159
Feature-map-level Online Adversarial Knowledge Distillation ICML 2020
MineGAN: effective knowledge transfer from GANs to target domains with few images CVPR 2020
Distilling portable Generative Adversarial Networks for Image Translation AAAI 2020
GAN Compression: Efficient Architectures for Interactive Conditional GANs CVPR 2020

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