Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics

Deep Residual Learning for Image Recognition

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ImageNet classification with deep convolutional neural networks

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

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Distinctive Image Features from Scale-Invariant Keypoints

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Densely Connected Convolutional Networks

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ImageNet Large Scale Visual Recognition Challenge

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Fully convolutional networks for semantic segmentation

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Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

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Unpaired image-to-image translation using cycle-consistent adversarial networks

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Image-to-Image Translation with Conditional Adversarial Networks

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Generative Adversarial Nets

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GAN（Generative Adversarial Nets）

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YOLOv3: An Incremental Improvement

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A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (Invited Paper)

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Overview of the High Efficiency Video Coding (HEVC) Standard

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Overview of the H.264/AVC video coding standard

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Two-Stream Convolutional Networks for Action Recognition in Videos

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Large-Scale Video Classification with Convolutional Neural Networks

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Progressive Growing of GANs for Improved Quality, Stability, and Variation

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High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

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Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

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Overview of the Scalable Video Coding Extension of the H.264/AVC Standard

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Deep Generative Image Models using a Laplacian Pyramid of Adversarial NetworksPreprint

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DualGAN: Unsupervised Dual Learning for Image-to-Image Translation

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Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks

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Unsupervised Learning of Video Representations using LSTMs

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The JPEG 2000 still image compression standard

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Rate-distortion optimization for video compression

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Learning to Discover Cross-Domain Relations with Generative Adversarial Networks

Kim, T., Cha, M., Kim, H., Lee, J. K., & Kim, J. (2017) · arXiv · doi:10.48550/arxiv.1703.05192 · Cited by 1,716 · see citing works

Long-Term Recurrent Convolutional Networks for Visual Recognition and Description

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End-to-end Optimized Image CompressionPreprint

Ballé, J., Laparra, V., & Simoncelli, E. P. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1611.01704 · Cited by 1,477 · see citing works

Variational image compression with a scale hyperpriorPreprint

Ballé, J., Minnen, D. C., Singh, S., Hwang, S. J., & Johnston, N. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.01436 · Cited by 1,368 · see citing works

Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform

Wang, X., Yu, K., Dong, C., & Loy, C. C. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00070 · Cited by 1,217 · see citing works

Deep multi-scale video prediction beyond mean square errorPreprint

Mathieu, M., Couprie, C., & LeCun, Y. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.05440 · Cited by 1,182 · see citing works

Taskonomy: Disentangling Task Transfer Learning

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MoCoGAN: Decomposing Motion and Content for Video Generation

Tulyakov, S., Liu, M.-Y., Yang, X., & Kautz, J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00165 · Cited by 1,076 · see citing works

Generating Videos with Scene DynamicsPreprint

Vondrick, C., Pirsiavash, H., & Torralba, A. B. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.02612 · Cited by 976 · see citing works

Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks

Lai, W., Huang, J., Ahuja, N., & Yang, M. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2865304 · Cited by 958 · see citing works

Full Resolution Image Compression with Recurrent Neural Networks

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Overview of fine granularity scalability in MPEG-4 video standard

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Deep Predictive Coding Networks for Video Prediction and Unsupervised LearningPreprint

Lotter, W. E., Kreiman, G., & Cox, D. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.08104 · Cited by 805 · see citing works

Unsupervised Learning for Physical Interaction through Video Prediction

Finn, C., Goodfellow, I., & Levine, S. (2016) · arXiv · doi:10.48550/arxiv.1605.07157 · Cited by 759 · see citing works

Pose Guided Person Image GenerationPreprint

Ma, L., Jia, X., Sun, Q., Schiele, B., Tuytelaars, T., & Gool, L. V. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1705.09368 · Cited by 708 · see citing works

Dynamic Filter Networks

Jia, X., Brabandere, B. D., Tuytelaars, T., & Gool, L. V. (2016) · neural information processing systems · Cited by 681 · see citing works

Stochastic Video Generation with a Learned PriorPreprint

Denton, E., & Fergus, R. (2018) · International Conference on Machine Learning · doi:10.48550/arxiv.1802.07687 · Cited by 599 · see citing works

PifPaf: Composite Fields for Human Pose Estimation

Kreiss, S., Bertoni, L., & Alahi, A. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.01225 · Cited by 574 · see citing works

Disentangled Person Image Generation

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Deformable GANs for Pose-Based Human Image Generation

Siarohin, A., Sangineto, E., Lathuilière, S., & Sebe, N. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00359 · Cited by 512 · see citing works

Decomposing Motion and Content for Natural Video Sequence Prediction

Villegas, R., Yang, J., Hong, S., Lin, X., & Lee, H. (2017) · arXiv · doi:10.48550/arxiv.1706.08033 · Cited by 488 · see citing works

Action-Conditional Video Prediction using Deep Networks in Atari GamesPreprint

Oh, J., Guo, X., Lee, H., Lewis, R. L., & Singh, S. P. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1507.08750 · Cited by 473 · see citing works

An Uncertain Future: Forecasting from Static Images Using Variational Autoencoders

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A Variational U-Net for Conditional Appearance and Shape Generation

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Dynamic Filter NetworksPreprint

Brabandere, B. D., Jia, X., Tuytelaars, T., & Gool, L. V. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.09673 · Cited by 461 · see citing works

Generating Videos with Scene Dynamics

Vondrick, C., Pirsiavash, H., & Torralba, A. (2016) · Maryland Shared Open Access Repository · doi:10.13016/m26gih-tnyz · Cited by 441 · see citing works

Variable Rate Image Compression with Recurrent Neural NetworksPreprint

Toderici, G. D., O’Malley, S. M., Hwang, S. J., Vincent, D., Minnen, D. C., Baluja, S., Covell, M., & Sukthankar, R. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.06085 · Cited by 441 · see citing works

MPEG-7 visual shape descriptors

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Temporal Generative Adversarial Nets with Singular Value Clipping

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Learning What and Where to DrawPreprint

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Learning Convolutional Networks for Content-Weighted Image Compression

Li, M., Zuo, W., Gu, S., Zhao, D., & Zhang, D. D. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00339 · Cited by 409 · see citing works

Stochastic Adversarial Video PredictionPreprint

Lee, A. X., Zhang, R., Ebert, F., Abbeel, P., Finn, C., & Levine, S. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1804.01523 · Cited by 357 · see citing works

Stochastic Variational Video PredictionPreprint

Babaeizadeh, M., Finn, C., Erhan, D., Campbell, R. H., & Levine, S. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1710.11252 · Cited by 351 · see citing works

Animating Arbitrary Objects via Deep Motion Transfer

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Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional NetworksPreprint

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Synthesizing Images of Humans in Unseen Poses

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Density Modeling of Images using a Generalized Normalization TransformationPreprint

Ballé, J., Laparra, V., & Simoncelli, E. P. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.06281 · Cited by 311 · see citing works

Mobile Visual Search

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Learning to Generate Long-term Future via Hierarchical PredictionPreprint

Villegas, R., Yang, J., Zou, Y., Sohn, S., Lin, X., & Lee, H. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.05831 · Cited by 279 · see citing works

End-to-end optimization of nonlinear transform codes for perceptual quality

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Spatio-Temporal Attention-Based LSTM Networks for 3D Action Recognition and Detection

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PKU-MMD

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Action-conditional video prediction using deep networks in Atari games

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Content-Aware Convolutional Neural Network for In-Loop Filtering in High Efficiency Video Coding

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CU Partition Mode Decision for HEVC Hardwired Intra Encoder Using Convolution Neural Network

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Location Discriminative Vocabulary Coding for Mobile Landmark Search

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CNN-based in-loop filtering for coding efficiency improvement

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Unsupervised Person Image Synthesis in Arbitrary Poses

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Dmcnn: Dual-Domain Multi-Scale Convolutional Neural Network for Compression Artifacts Removal

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Compressed Histogram of Gradients: A Low-Bitrate Descriptor

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Overview of the MPEG-CDVS Standard

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Toward Intelligent Sensing: Intermediate Deep Feature Compression

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Hybrid Coding of Pictorial Data

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Tree Histogram Coding for Mobile Image Matching

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Hierarchical Long-term Video Prediction without SupervisionPreprint

Wichers, N., Villegas, R., Erhan, D., & Lee, H. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.04768 · Cited by 96 · see citing works

A Benchmark Dataset and Comparison Study for Multi-modal Human Action Analytics

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Compact Descriptors for Video Analysis: The Emerging MPEG Standard

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Enhanced Motion-Compensated Video Coding With Deep Virtual Reference Frame Generation

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Lossy Intermediate Deep Learning Feature Compression and Evaluation

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Towards Coding For Human And Machine Vision: A Scalable Image Coding Approach

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Near-Lossless Deep Feature Compression for Collaborative Intelligence

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FUTUREGAN: ANTICIPATING THE FUTURE FRAMES OF VIDEO SEQUENCES USING SPATIO-TEMPORAL 3D CONVOLUTIONS IN PROGRESSIVELY GROWING GANS

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Non-local Attention Optimized Deep Image CompressionPreprint

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One-for-All: Grouped Variation Network-Based Fractional Interpolation in Video Coding

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Progressive Spatial Recurrent Neural Network for Intra Prediction

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Jointly Embedding Multiple Single-Cell Omics Measurements

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Context-Adaptive Neural Network-Based Prediction for Image Compression

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Multi-Modality Multi-Task Recurrent Neural Network for Online Action Detection

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Learned Video Compression via Joint Spatial-Temporal Correlation Exploration

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Transformation-Based Models of Video SequencesPreprint

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Location coding for mobile image retrieval

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AVS2 ? Making Video Coding Smarter [Standards in a Nutshell]

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Dense Residual Convolutional Neural Network based In-Loop Filter for HEVC

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Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications

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Learning End-to-End Lossy Image Compression: A Benchmark

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Scalable Image Coding for Humans and Machines

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Towards Coding for Human and Machine Vision: Scalable Face Image Coding

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Towards Analysis-Friendly Face Representation With Scalable Feature and Texture Compression

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SSSIC: Semantics-to-Signal Scalable Image Coding With Learned Structural Representations

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Collaborative Intelligence: Challenges and Opportunities

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Video Coding for Machines: Compact Visual Representation Compression for Intelligent Collaborative Analytics

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Image Coding for Machines with Omnipotent Feature Learning

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Large Models for Aerial Edges: An Edge-Cloud Model Evolution and Communication Paradigm

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Comprehensive Study of Compression and Texture Integration for Digital Imaging and Communications in Medicine Data Analysis

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Towards Task-Generic Image Compression: A Study of Semantics-Oriented Metrics

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Digital Retina: A Way to Make the City Brain More Efficient by Visual Coding

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AdaMask: Enabling Machine-Centric Video Streaming with Adaptive Frame Masking for DNN Inference Offloading

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A Coding Framework and Benchmark Towards Low-Bitrate Video Understanding

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End-to-End Compression Towards Machine Vision: Network Architecture Design and Optimization

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USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020s

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Latent-Space Scalability for Multi-Task Collaborative Intelligence

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Recent Standard Development Activities on Video Coding for MachinesPreprint

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VNVC: A Versatile Neural Video Coding Framework for Efficient Human-Machine Vision

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Non-Semantics Suppressed Mask Learning for Unsupervised Video Semantic Compression

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DeepSVC: Deep Scalable Video Coding for Both Machine and Human Vision

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Image and Video Coding Techniques for Ultra-low Latency

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In-Home Older Adults’ Activity Pattern Monitoring Using Depth Sensors: A Review

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Improving Multiple Machine Vision Tasks in the Compressed Domain

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Human–Machine Interaction-Oriented Image Coding for Resource-Constrained Visual Monitoring in IoT

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FitVid: Overfitting in Pixel-Level Video PredictionPreprint

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Biologically Inspired Machine Learning-Based Trajectory Analysis in Intelligent Dispatching Energy Storage System

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Boosting Neural Image Compression for Machines Using Latent Space Masking

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Unified Architecture Adaptation for Compressed Domain Semantic Inference

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An Emerging Coding Paradigm Vcm: A Scalable Coding Approach Beyond Feature And Signal

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Data Representation in Hybrid Coding Framework for Feature Maps Compression

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2C-Net: integrate image compression and classification via deep neural network

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Unveiling the Future of Human and Machine Coding: A Survey of End-to-End Learned Image Compression

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Deep Feature Compression Using Spatio-Temporal Arrangement Toward Collaborative Intelligent World

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ICMH-Net: Neural Image Compression Towards both Machine Vision and Human Vision

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Scalable Face Image Coding via StyleGAN Prior: Toward Compression for Human-Machine Collaborative Vision

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Task-Driven Video Compression for Humans and Machines: Framework Design and Optimization

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Accuracy Improvement of Object Detection in VVC Coded Video Using YOLO-v7 Features

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Learning in Compressed Domain for Faster Machine Vision Tasks

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Progressive Deep Image Compression for Hybrid Contexts of Image Classification and Reconstruction

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Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative AnalyticsPreprint

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