{"total":71,"rows":[{"id":"2404.09458","title":"CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splatting","created":"2024-04-15","cited_by_count":82,"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":"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":"2409.08481","title":"USTC-TD: A Test Dataset and Benchmark for Image and Video Coding in 2020s","created":"2024-09-13","cited_by_count":37,"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":"2503.01428","title":"DLF: Extreme Image Compression with Dual-generative Latent Fusion","created":"2025-03-03","cited_by_count":21,"area":null},{"id":"2404.13372","title":"HybridFlow: Infusing Continuity into Masked Codebook for Extreme Low-Bitrate Image Compression","created":"2024-04-20","cited_by_count":14,"area":null},{"id":"2412.00505","title":"Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion","created":"2024-11-30","cited_by_count":13,"area":null},{"id":"2503.01505","title":"Lossy Neural Compression for Geospatial Analytics: A Review","created":"2025-03-03","cited_by_count":10,"area":null},{"id":"2403.00628","title":"Region-Adaptive Transform with Segmentation Prior for Image Compression","created":"2024-03-01","cited_by_count":8,"area":null},{"id":"2407.10632","title":"Bidirectional Stereo Image Compression with Cross-Dimensional Entropy Model","created":"2024-07-15","cited_by_count":8,"area":null},{"id":"2411.16119","title":"Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression","created":"2024-11-25","cited_by_count":8,"area":null},{"id":"2505.09193","title":"BiECVC: Gated Diversification of Bidirectional Contexts for Learned Video Compression","created":"2025-05-14","cited_by_count":8,"area":null},{"id":"2406.06165","title":"Generalized Nested Latent Variable Models for Lossy Coding applied to Wind Turbine Scenarios","created":"2024-06-10","cited_by_count":7,"area":null},{"id":"2504.16953","title":"TVC: Tokenized Video Compression with Ultra-Low Bit Rate","created":"2025-04-22","cited_by_count":7,"area":null},{"id":"2304.09571","title":"LLIC: Large Receptive Field Transform Coding with Adaptive Weights for Learned Image Compression","created":"2023-04-19","cited_by_count":6,"area":null},{"id":"2405.01170","title":"GroupedMixer: An Entropy Model with Group-wise Token-Mixers for Learned Image Compression","created":"2024-05-02","cited_by_count":6,"area":null},{"id":"2512.00877","title":"Feed-Forward 3D Gaussian Splatting Compression with Long-Context Modeling","created":"2025-11-30","cited_by_count":6,"area":null},{"id":"2403.17677","title":"Onboard deep lossless and near-lossless predictive coding of hyperspectral images with line-based attention","created":"2024-03-26","cited_by_count":5,"area":null},{"id":"2408.12150","title":"DeepHQ: Learned Hierarchical Quantizer for Progressive Deep Image Coding","created":"2024-08-22","cited_by_count":5,"area":null},{"id":"2502.20161","title":"Balanced Rate-Distortion Optimization in Learned Image Compression","created":"2025-02-27","cited_by_count":5,"area":null},{"id":"2412.00437","title":"DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression","created":"2024-11-30","cited_by_count":4,"area":null},{"id":"2506.01221","title":"Flexible Mixed Precision Quantization for Learned Image Compression","created":"2025-06-02","cited_by_count":4,"area":null},{"id":"2405.10244","title":"Towards Task-Compatible Compressible Representations","created":"2024-05-16","cited_by_count":3,"area":null},{"id":"2410.12191","title":"Test-time adaptation for image compression with distribution regularization","created":"2024-10-16","cited_by_count":3,"area":null},{"id":"2411.10773","title":"An End-to-End Real-World Camera Imaging Pipeline","created":"2024-11-16","cited_by_count":3,"area":null},{"id":"2401.08154","title":"TLIC: Learned Image Compression with ROI-Weighted Distortion and Bit Allocation","created":"2024-01-16","cited_by_count":2,"area":null},{"id":"2411.09308","title":"DT-JRD: Deep Transformer based Just Recognizable Difference Prediction Model for Video Coding for Machines","created":"2024-11-14","cited_by_count":2,"area":null},{"id":"2412.15752","title":"Sparse Point Clouds Assisted Learned Image Compression","created":"2024-12-20","cited_by_count":2,"area":null},{"id":"2502.16795","title":"Continuous Patch Stitching for Block-wise Image Compression","created":"2025-02-24","cited_by_count":2,"area":null},{"id":"2504.04658","title":"3DM-WeConvene: Learned Image Compression with 3D Multi-Level Wavelet-Domain Convolution and Entropy Model","created":"2025-04-07","cited_by_count":2,"area":null},{"id":"2510.22943","title":"Switchable Token-Specific Codebook Quantization For Face Image Compression","created":"2025-10-27","cited_by_count":2,"area":null},{"id":"2601.20769","title":"Leveraging Second-Order Curvature for Efficient Learned Image Compression: Theory and Empirical Evidence","created":"2026-01-28","cited_by_count":2,"area":null},{"id":"2402.00680","title":"LVC-LGMC: Joint Local and Global Motion Compensation for Learned Video Compression","created":"2024-02-01","cited_by_count":1,"area":null},{"id":"2409.11111","title":"Few-Shot Domain Adaptation for Learned Image Compression","created":"2024-09-17","cited_by_count":1,"area":null},{"id":"2410.18083","title":"FIPER: Factorized Features for Robust Image Super-Resolution and Compression","created":"2024-10-23","cited_by_count":1,"area":null},{"id":"2411.16727","title":"An Information-Theoretic Regularizer for Lossy Neural Image Compression","created":"2024-11-23","cited_by_count":1,"area":null},{"id":"2503.06399","title":"FEDS: Feature and Entropy-Based Distillation Strategy for Efficient Learned Image Compression","created":"2025-03-09","cited_by_count":1,"area":null},{"id":"2503.23862","title":"Learned Image Compression and Restoration for Digital Pathology","created":"2025-03-31","cited_by_count":1,"area":null},{"id":"2504.12997","title":"All-in-One Transferring Image Compression from Human Perception to Multi-Machine Perception","created":"2025-04-17","cited_by_count":1,"area":null},{"id":"2506.01229","title":"Structured Pruning and Quantization for Learned Image Compression","created":"2025-06-02","cited_by_count":1,"area":null},{"id":"2506.09510","title":"Generalized Gaussian Entropy Model for Point Cloud Attribute Compression with Dynamic Likelihood Intervals","created":"2025-06-11","cited_by_count":1,"area":null},{"id":"2509.07704","title":"SEEC: Segmentation-Assisted Multi-Entropy Models for Learned Lossless Image Compression","created":"2025-09-09","cited_by_count":1,"area":null},{"id":"2510.20331","title":"AnyPcc: Compressing Any Point Cloud with a Single Universal Model","created":"2025-10-23","cited_by_count":1,"area":null},{"id":"2510.24437","title":"Deeply-Conditioned Image Compression via Self-Generated Priors","created":"2025-10-28","cited_by_count":1,"area":null},{"id":"2603.13864","title":"Inevitable Encounters: Backdoor Attacks Involving Lossy Compression","created":"2026-03-14","cited_by_count":1,"area":null},{"id":"2603.25316","title":"Adaptive Learned Image Compression with Graph Neural Networks","created":"2026-03-26","cited_by_count":1,"area":null},{"id":"2307.02273","title":"Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression","created":"2023-07-05","cited_by_count":0,"area":null},{"id":"2308.08723","title":"Dynamic Kernel-Based Adaptive Spatial Aggregation for Learned Image Compression","created":"2023-08-17","cited_by_count":0,"area":null},{"id":"2401.13616","title":"FLLIC: Functionally Lossless Image Compression","created":"2024-01-24","cited_by_count":0,"area":null},{"id":"2405.10518","title":"Enhancing Perception Quality in Remote Sensing Image Compression via Invertible Neural Network","created":"2024-05-17","cited_by_count":0,"area":null},{"id":"2409.04013","title":"3D-LMVIC: Learning-based Multi-View Image Coding with 3D Gaussian Geometric Priors","created":"2024-09-06","cited_by_count":0,"area":null},{"id":"2412.11771","title":"Point Cloud-Assisted Neural Image Compression","created":"2024-12-16","cited_by_count":0,"area":null},{"id":"2502.00700","title":"S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression","created":"2025-02-02","cited_by_count":0,"area":null},{"id":"2502.14937","title":"Compact Latent Representation for Image Compression (CLRIC)","created":"2025-02-20","cited_by_count":0,"area":null},{"id":"2504.21778","title":"LoC-LIC: Low Complexity Learned Image Coding Using Hierarchical Feature Transforms","created":"2025-04-30","cited_by_count":0,"area":null},{"id":"2506.21851","title":"End-to-End RGB-IR Joint Image Compression With Channel-wise Cross-modality Entropy Model","created":"2025-06-27","cited_by_count":0,"area":null},{"id":"2511.08009","title":"From Noise to Latent: Generating Gaussian Latents for INR-Based Image Compression","created":"2025-11-11","cited_by_count":0,"area":null},{"id":"2511.13922","title":"Self-Supervised Compression and Artifact Correction for Streaming Underwater Imaging Sonar","created":"2025-11-17","cited_by_count":0,"area":null},{"id":"2512.07192","title":"HyperVQ: Enabling Hyperprior Entropy Modeling for VQ-Based Generative Image Compression","created":"2025-12-08","cited_by_count":0,"area":null},{"id":"2512.16743","title":"TreeNet: A Light Weight Model for Low Bitrate Image Compression","created":"2025-12-18","cited_by_count":0,"area":null},{"id":"2512.24463","title":"Spectral and Spatial Graph Learning for Multispectral Solar Image Compression","created":"2025-12-30","cited_by_count":0,"area":null},{"id":"2601.06059","title":"Context Video Semantic Transmission with Variable Length and Rate Coding over MIMO Channels","created":"2025-12-23","cited_by_count":0,"area":null},{"id":"2601.22002","title":"Understanding Rate-Distortion Performance in Distributed Transformer Inference","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2603.06766","title":"HiDE: Hierarchical Dictionary-Based Entropy Modeling for Learned Image Compression","created":"2026-03-06","cited_by_count":0,"area":null},{"id":"2604.05347","title":"CI-ICM: Channel Importance-driven Learned Image Coding for Machines","created":"2026-04-07","cited_by_count":0,"area":null},{"id":"2606.00111","title":"ChWDTA: Channel-wise Wavelet-Domain Transformer Attention and Entropy Modeling for Learned Image Compression","created":"2026-05-27","cited_by_count":0,"area":null},{"id":"2608.01653","title":"Hadamard-Domain Model Quantization for Learned Image Coding","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2608.10952","title":"Multiple Scale Latents for Learned Image Compression","created":"2026-08-11","cited_by_count":0,"area":null},{"id":"2609.04274","title":"Multi-scale Image Representation Compression","created":"2026-09-02","cited_by_count":0,"area":null},{"id":"2609.09020","title":"PIC: Revisiting INR for Image Coding with Fast Encoding and Sub-Millisecond Decoding","created":"2026-09-08","cited_by_count":0,"area":null}],"next_cursor":null}