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20232026
most citedControllable Distortion-Perception Tradeoff Through Latent Diffusion for Neural Image Compression

2 citations · 5 across the 13 of their papers we have counts for

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eess.IV2025

A Multi-Grid Implicit Neural Representation for Multi-View Videos

Qingyue Ling, Zhengxue Cheng, Donghui Feng +6

Multi-view videos are becoming widely used in different fields, but their high resolution and multi-camera shooting raise significant challenges for storage and transmission. In th…

cs.CV2025

Content-Aware Mamba for Learned Image Compression

Yunuo Chen, Zezheng Lyu, Bing He +6

Recent learned image compression (LIC) leverages Mamba-style state-space models (SSMs) for global receptive fields with linear complexity. However, the standard Mamba adopts conten…

cs.CV2025

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression

Yunuo Chen, Qian Li, Bing He +6

Transformer-based Learned Image Compression (LIC) suffers from a suboptimal trade-off between decoding latency and rate-distortion (R-D) performance. Moreover, the critical role of…

cs.CV2025★ 1 cited

Linear Attention Modeling for Learned Image Compression

Donghui Feng, Zhengxue Cheng, Shen Wang +4

Recent years, learned image compression has made tremendous progress to achieve impressive coding efficiency. Its coding gain mainly comes from non-linear neural network-based tran…

eess.IV2025

Large Language Model for Lossless Image Compression with Visual Prompts

Junhao Du, Chuqin Zhou, Ning Cao +6

Recent advancements in deep learning have driven significant progress in lossless image compression. With the emergence of Large Language Models (LLMs), preliminary attempts have b…