{"total":696,"rows":[{"id":"2103.03230","title":"Barlow Twins: Self-Supervised Learning via Redundancy Reduction","created":"2021-03-04","cited_by_count":1838,"area":null},{"id":"2210.13438","title":"High Fidelity Neural Audio Compression","created":"2022-10-24","cited_by_count":687,"area":null},{"id":"2309.15505","title":"Finite Scalar Quantization: VQ-VAE Made Simple","created":"2023-09-27","cited_by_count":440,"area":null},{"id":"2203.10886","title":"ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding","created":"2022-03-21","cited_by_count":301,"area":null},{"id":"2109.15047","title":"Deep Contextual Video Compression","created":"2021-09-30","cited_by_count":221,"area":null},{"id":"2303.14978","title":"Learned Image Compression with Mixed Transformer-CNN Architectures","created":"2023-03-27","cited_by_count":211,"area":null},{"id":"2103.15306","title":"Checkerboard Context Model for Efficient Learned Image Compression","created":"2021-03-29","cited_by_count":202,"area":null},{"id":"2201.12204","title":"From data to functa: Your data point is a function and you can treat it like one","created":"2022-01-28","cited_by_count":187,"area":null},{"id":"2207.09353","title":"Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications","created":"2022-07-19","cited_by_count":175,"area":null},{"id":"2112.04267","title":"Implicit Neural Representations for Image Compression","created":"2021-12-08","cited_by_count":162,"area":null},{"id":"2105.09600","title":"FVC: A New Framework towards Deep Video Compression in Feature Space","created":"2021-05-20","cited_by_count":153,"area":null},{"id":"2203.08450","title":"The Devil Is in the Details: Window-based Attention for Image Compression","created":"2022-03-16","cited_by_count":147,"area":null},{"id":"2207.05894","title":"Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compression","created":"2022-07-13","cited_by_count":128,"area":null},{"id":"2103.04505","title":"Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges","created":"2021-03-08","cited_by_count":115,"area":"inference"},{"id":"2202.05492","title":"Entroformer: A Transformer-based Entropy Model for Learned Image Compression","created":"2022-02-11","cited_by_count":107,"area":null},{"id":"2108.03690","title":"Enhanced Invertible Encoding for Learned Image Compression","created":"2021-08-08","cited_by_count":105,"area":null},{"id":"2310.10325","title":"Towards image compression with perfect realism at ultra-low bitrates","created":"2023-10-16","cited_by_count":103,"area":null},{"id":"2403.08551","title":"GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting","created":"2024-03-13","cited_by_count":99,"area":null},{"id":"2301.11189","title":"Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models","created":"2023-01-26","cited_by_count":94,"area":null},{"id":"2201.01389","title":"Semantic Communications: Principles and Challenges","created":"2021-12-30","cited_by_count":91,"area":null},{"id":"2206.08889","title":"Lossy Compression with Gaussian Diffusion","created":"2022-06-17","cited_by_count":90,"area":"diffusion"},{"id":"2106.02466","title":"Graph Barlow Twins: A self-supervised representation learning framework for graphs","created":"2021-06-04","cited_by_count":85,"area":null},{"id":"2211.07273","title":"MLIC: Multi-Reference Entropy Model for Learned Image Compression","created":"2022-11-14","cited_by_count":84,"area":null},{"id":"2201.12904","title":"COIN++: Neural Compression Across Modalities","created":"2022-01-30","cited_by_count":82,"area":null},{"id":"2404.09458","title":"CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splatting","created":"2024-04-15","cited_by_count":82,"area":null},{"id":"2502.14831","title":"Improving the Diffusability of Autoencoders","created":"2025-02-20","cited_by_count":80,"area":"diffusion"},{"id":"2202.06533","title":"An Introduction to Neural Data Compression","created":"2022-02-14","cited_by_count":79,"area":null},{"id":"2112.10961","title":"Nonlinear Transform Source-Channel Coding for Semantic Communications","created":"2021-12-21","cited_by_count":76,"area":null},{"id":"2406.01597","title":"End-to-End Rate-Distortion Optimized 3D Gaussian Representation","created":"2024-04-09","cited_by_count":75,"area":null},{"id":"2307.01944","title":"Text + Sketch: Image Compression at Ultra Low Rates","created":"2023-07-04","cited_by_count":67,"area":null},{"id":"2111.06707","title":"Transformer-based Image Compression","created":"2021-11-12","cited_by_count":62,"area":null},{"id":"2105.02158","title":"VoxelContext-Net: An Octree based Framework for Point Cloud Compression","created":"2021-05-05","cited_by_count":61,"area":null},{"id":"2404.18820","title":"Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Prior","created":"2024-04-29","cited_by_count":60,"area":"diffusion"},{"id":"2203.02194","title":"Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection","created":"2022-03-04","cited_by_count":59,"area":null},{"id":"2108.09551","title":"Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform","created":"2021-08-21","cited_by_count":58,"area":null},{"id":"2307.15421","title":"MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compression","created":"2023-07-28","cited_by_count":58,"area":null},{"id":"2206.07460","title":"Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Prediction","created":"2022-06-15","cited_by_count":55,"area":null},{"id":"2312.02753","title":"C3: High-performance and low-complexity neural compression from a single image or video","created":"2023-12-05","cited_by_count":55,"area":null},{"id":"2112.04487","title":"Joint Global and Local Hierarchical Priors for Learned Image Compression","created":"2021-12-08","cited_by_count":54,"area":null},{"id":"2404.02903","title":"LidarDM: Generative LiDAR Simulation in a Generated World","created":"2024-04-03","cited_by_count":54,"area":null},{"id":"2106.10800","title":"Lossy Compression for Lossless Prediction","created":"2021-06-21","cited_by_count":52,"area":null},{"id":"2104.05168","title":"Soft then Hard: Rethinking the Quantization in Neural Image Compression","created":"2021-04-12","cited_by_count":51,"area":null},{"id":"2201.00057","title":"Optimal Representations for Covariate Shift","created":"2021-12-31","cited_by_count":51,"area":null},{"id":"2212.14593","title":"NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling","created":"2022-12-30","cited_by_count":51,"area":null},{"id":"2205.13129","title":"Wireless Deep Video Semantic Transmission","created":"2022-05-26","cited_by_count":50,"area":null},{"id":"2302.05071","title":"EVC: Towards Real-Time Neural Image Compression with Mask Decay","created":"2023-02-10","cited_by_count":49,"area":null},{"id":"2207.05315","title":"CANF-VC: Conditional Augmented Normalizing Flows for Video Compression","created":"2022-07-12","cited_by_count":46,"area":null},{"id":"2104.09987","title":"Differentiable Model Compression via Pseudo Quantization Noise","created":"2021-04-20","cited_by_count":45,"area":null},{"id":"2203.02452","title":"Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression","created":"2022-03-04","cited_by_count":45,"area":null},{"id":"2203.10897","title":"Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression","created":"2022-03-21","cited_by_count":43,"area":null},{"id":"2109.03082","title":"Perceptual Learned Video Compression with Recurrent Conditional GAN","created":"2021-09-07","cited_by_count":41,"area":null},{"id":"2305.18378","title":"Disentanglement via Latent Quantization","created":"2023-05-28","cited_by_count":40,"area":null},{"id":"2312.05355","title":"Neither hype nor gloom do DNNs justice","created":"2023-12-08","cited_by_count":40,"area":null},{"id":"2103.15726","title":"Slimmable Compressive Autoencoders for Practical Neural Image Compression","created":"2021-03-29","cited_by_count":39,"area":null},{"id":"2204.12684","title":"Density-preserving Deep Point Cloud Compression","created":"2022-04-27","cited_by_count":39,"area":null},{"id":"2208.04094","title":"Towards Semantic Communications: Deep Learning-Based Image Semantic Coding","created":"2022-08-08","cited_by_count":36,"area":null},{"id":"2404.08580","title":"Lossy Image Compression with Foundation Diffusion Models","created":"2024-04-12","cited_by_count":36,"area":"diffusion"},{"id":"2107.06463","title":"Learned Image Compression with Gaussian-Laplacian-Logistic Mixture Model and Concatenated Residual Modules","created":"2021-07-14","cited_by_count":35,"area":null},{"id":"2407.01866","title":"Image-GS: Content-Adaptive Image Representation via 2D Gaussians","created":"2024-07-02","cited_by_count":35,"area":null},{"id":"2412.01615","title":"OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarking","created":"2024-12-02","cited_by_count":35,"area":null},{"id":"2110.12805","title":"Algorithms for the Communication of Samples","created":"2021-10-25","cited_by_count":34,"area":null},{"id":"2212.07372","title":"Image Compression with Product Quantized Masked Image Modeling","created":"2022-12-14","cited_by_count":33,"area":null},{"id":"2506.21977","title":"StableCodec: Taming One-Step Diffusion for Extreme Image Compression","created":"2025-06-27","cited_by_count":33,"area":"diffusion"},{"id":"2102.11026","title":"High-order Differentiable Autoencoder for Nonlinear Model Reduction","created":"2021-02-19","cited_by_count":32,"area":null},{"id":"2302.08899","title":"QARV: Quantization-Aware ResNet VAE for Lossy Image Compression","created":"2023-02-16","cited_by_count":32,"area":null},{"id":"2108.11898","title":"Supervised Compression for Resource-Constrained Edge Computing Systems","created":"2021-08-21","cited_by_count":31,"area":null},{"id":"2207.01932","title":"Image Coding for Machines with Omnipotent Feature Learning","created":"2022-07-05","cited_by_count":31,"area":null},{"id":"2309.15848","title":"SHACIRA: Scalable HAsh-grid Compression for Implicit Neural Representations","created":"2023-09-27","cited_by_count":31,"area":null},{"id":"2203.04963","title":"Neural Data-Dependent Transform for Learned Image Compression","created":"2022-03-09","cited_by_count":30,"area":null},{"id":"2210.00933","title":"Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop","created":"2022-10-03","cited_by_count":30,"area":null},{"id":"2504.00496","title":"Learned Image Compression with Dictionary-based Entropy Model","created":"2025-04-01","cited_by_count":30,"area":null},{"id":"2401.08920","title":"Idempotence and Perceptual Image Compression","created":"2024-01-17","cited_by_count":29,"area":null},{"id":"2402.18152","title":"Boosting Neural Representations for Videos with a Conditional Decoder","created":"2024-02-28","cited_by_count":29,"area":null},{"id":"2112.09529","title":"End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video Compression","created":"2021-12-17","cited_by_count":28,"area":null},{"id":"2405.15413","title":"MambaVC: Learned Visual Compression with Selective State Spaces","created":"2024-05-24","cited_by_count":28,"area":"ssm"},{"id":"2502.01189","title":"Compressed Image Generation with Denoising Diffusion Codebook Models","created":"2025-02-03","cited_by_count":28,"area":"diffusion"},{"id":"2106.02782","title":"On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework","created":"2021-06-05","cited_by_count":27,"area":null},{"id":"2407.09853","title":"Image Compression for Machine and Human Vision with Spatial-Frequency Adaptation","created":"2024-07-13","cited_by_count":26,"area":null},{"id":"2505.16091","title":"OSCAR: One-Step Diffusion Codec Across Multiple Bit-rates","created":"2025-05-22","cited_by_count":26,"area":"diffusion"},{"id":"2505.16687","title":"One-Step Diffusion-Based Image Compression with Semantic Distillation","created":"2025-05-22","cited_by_count":26,"area":"diffusion"},{"id":"2102.08329","title":"An Information-Theoretic Justification for Model Pruning","created":"2021-02-16","cited_by_count":25,"area":null},{"id":"2112.06334","title":"DPICT: Deep Progressive Image Compression Using Trit-Planes","created":"2021-12-12","cited_by_count":25,"area":null},{"id":"2112.08691","title":"Towards Robust Neural Image Compression: Adversarial Attack and Model Finetuning","created":"2021-12-16","cited_by_count":25,"area":null},{"id":"2305.19185","title":"Compression with Bayesian Implicit Neural Representations","created":"2023-05-30","cited_by_count":25,"area":null},{"id":"2501.03399","title":"Compression of 3D Gaussian Splatting with Optimized Feature Planes and Standard Video Codecs","created":"2025-01-06","cited_by_count":25,"area":null},{"id":"2505.16177","title":"Generative Latent Coding for Ultra-Low Bitrate Image and Video Compression","created":"2025-05-22","cited_by_count":25,"area":null},{"id":"2102.02913","title":"Progressive Neural Image Compression with Nested Quantization and Latent Ordering","created":"2021-02-04","cited_by_count":24,"area":null},{"id":"2103.06089","title":"Variable-rate discrete representation learning","created":"2021-03-10","cited_by_count":24,"area":null},{"id":"2104.12456","title":"3D Scene Compression through Entropy Penalized Neural Representation Functions","created":"2021-04-26","cited_by_count":23,"area":null},{"id":"2203.09208","title":"Neural Compression-Based Feature Learning for Video Restoration","created":"2022-03-17","cited_by_count":23,"area":null},{"id":"2304.06244","title":"Computationally-Efficient Neural Image Compression with Shallow Decoders","created":"2023-04-13","cited_by_count":23,"area":null},{"id":"2305.17105","title":"Random-Access Neural Compression of Material Textures","created":"2023-05-26","cited_by_count":23,"area":null},{"id":"2401.15864","title":"Spatial Decomposition and Temporal Fusion based Inter Prediction for Learned Video Compression","created":"2024-01-29","cited_by_count":23,"area":null},{"id":"2403.02944","title":"Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity","created":"2024-03-05","cited_by_count":23,"area":null},{"id":"2406.02328","title":"SimpleSpeech: Towards Simple and Efficient Text-to-Speech with Scalar Latent Transformer Diffusion Models","created":"2024-06-04","cited_by_count":23,"area":"diffusion"},{"id":"2410.02640","title":"RDEIC: Accelerating Diffusion-Based Extreme Image Compression with Relay Residual Diffusion","created":"2024-10-03","cited_by_count":23,"area":"diffusion"},{"id":"2502.05741","title":"Linear Attention Modeling for Learned Image Compression","created":"2025-02-09","cited_by_count":23,"area":null},{"id":"2512.20194","title":"Generative Latent Coding for Ultra-Low Bitrate Image Compression","created":"2025-12-23","cited_by_count":23,"area":null},{"id":"2203.09931","title":"3DAC: Learning Attribute Compression for Point Clouds","created":"2022-03-17","cited_by_count":22,"area":null},{"id":"2209.04847","title":"Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression","created":"2022-09-11","cited_by_count":22,"area":null}],"next_cursor":"100"}