20 citations · 22 across the 9 of their papers we have counts for
9 papers
Practical Lossless Volumetric Medical Image Compression via Tri-plane Context Tree Learning
Yuanchao Bai, Yifan Zhao, Kai Wang +5
Lossless compression of volumetric medical images is of paramount importance for clinical and research applications where data fidelity is essential. Traditional compression method…
Graph-Guided Adaptive Channel Elimination for KV Cache Compression
Enwei Tong, Yao Zhu, Yuanchao Bai +3
Large Language Models have revolutionized natural language processing, achieving unprecedented success across a vast range of tasks. However, their practical application in long-co…
ControlFoley: Unified and Controllable Video-to-Audio Generation with Cross-Modal Conflict Handling
Jianxuan Yang, Xinyue Guo, Zhi Cheng +10
Recent advances in video-to-audio (V2A) generation enable high-quality audio synthesis from visual content, yet achieving robust and fine-grained controllability remains challengin…
Rethinking Autoregressive Models for Lossless Image Compression via Hierarchical Parallelism and Progressive Adaptation
Daxin Li, Yuanchao Bai, Kai Wang +3
Autoregressive (AR) models, the theoretical performance benchmark for learned lossless image compression, are often dismissed as impractical due to prohibitive computational cost.…
CALLIC: Content Adaptive Learning for Lossless Image Compression
Daxin Li, Yuanchao Bai, Kai Wang +3
Learned lossless image compression has achieved significant advancements in recent years. However, existing methods often rely on training amortized generative models on massive da…
Learning Lossless Compression for High Bit-Depth Volumetric Medical Image
Kai Wang, Yuanchao Bai, Daxin Li +3
Recent advances in learning-based methods have markedly enhanced the capabilities of image compression. However, these methods struggle with high bit-depth volumetric medical image…
GroupedMixer: An Entropy Model with Group-wise Token-Mixers for Learned Image Compression
Daxin Li, Yuanchao Bai, Kai Wang +3
Transformer-based entropy models have gained prominence in recent years due to their superior ability to capture long-range dependencies in probability distribution estimation comp…
Semantic Ensemble Loss and Latent Refinement for High-Fidelity Neural Image Compression
Daxin Li, Yuanchao Bai, Kai Wang +2
Recent advancements in neural compression have surpassed traditional codecs in PSNR and MS-SSIM measurements. However, at low bit-rates, these methods can introduce visually disple…
Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression
Yuanchao Bai, Xianming Liu, Kai Wang +3
Lossless and near-lossless image compression is of paramount importance to professional users in many technical fields, such as medicine, remote sensing, precision engineering and…