The paper introduces PRESLEY, an end‑to‑end video streaming pipeline that uses generative AI layers to selectively degrade and restore less important regions of a frame. By replacing destructive block removal with adaptive in‑place degradation and signaling block strength via a side channel, PRESLEY achieves significant bitrate savings and improved background quality compared to its predecessor and pristine baselines. The authors also analyze the theoretical headroom of this architecture, quantifying remaining cost‑axis headroom and modeling post‑restoration damage to guide future rate‑distortion‑restoration selection.
By Emanuele Artioli, Farzad Tashtarian, Christian Timmerer
arXiv:2609.18302v1 Announce Type: new
Abstract: RAW-to-sRGB image signal processing (ISP) must recover perceptually faithful colors and fine details from sensor measurements, often under imperfect sp...
By Tailai Chen, Xiaotong Luo, Yuan Gao, Xin Jin, Wenjun Zeng
The paper introduces UniGVC, a unified generative video codec that supports both low‑delay streaming and high‑quality playback from a single bitstream. It offers two decoding modes: UniGVC‑BI, a bidirectional diffusion model with dense attention for quality‑oriented random‑access decoding, and UniGVC‑AR, a windowed autoregressive diffusion model for low‑delay streaming. Both modes share a hierarchical latent codec that produces ultra‑low‑bitrate conditions, enabling the BI model to act as a teacher for distilling the AR model, while a lightweight conditional decoder further reduces streaming latency.
By Tianyu Zhang, Shuai Huo, Dengchao Jin, Hewei Liu, Meng Lei, Tianwen Wu, Jiawen Gu, Chao Zhou, Li Li, Dong Liu
arXiv:2610.09125v1 Announce Type: new
Abstract: Reference-based object compositing inserts or replaces an object using a background image, a reference image, and a 2D compositing mask. These inputs g...
By Sanghyun Jo, Chae Yeon Lim, Donghwan Lee, Sihyun Kim, Soo Ye Kim, Kyungsu Kim
arXiv:2607.22380v3 Announce Type: replace
Abstract: Infrared multi-frame super-resolution (MFSR) exploits complementary observations to recover spatial detail, but its evaluation remains fragmented a...
By Jie Deng, Heyang Wang, Changxin Wang, Junkai Shen, Hongyi Chen, Zhiping He, Hongxing Qi, Xudong Zhang, Jianyu Wang
arXiv:2609.27274v1 Announce Type: new
Abstract: Due to the limited dynamic range of conventional image sensors, captured low dynamic range (LDR) video often suffers from highlight clipping and shadow...
By Tao Zhang, Peixian Su, Xingyu Gao, Yunhao Zou, Yu Lu, Zunjie Zhu, Bolun Zheng, Ying Fu, Chenggang Yan
arXiv:2609.36929v1 Announce Type: new
Abstract: Recent event-based depth estimation methods successfully transfer geometric priors from vision foundation models via cross-modal distillation. However,...
By Thai Duy Nguyen, Addison Lin Wang
Due to the limited dynamic range of conventional image sensors, captured low dynamic range (LDR) video often suffers from highlight clipping and shadow detail loss, making high-quality high dynamic ra...
LayerRecall is a memory router for autoregressive video diffusion that selectively retrieves and injects historical key/value states into specific layers of the model, based on the current context. It addresses the problem that existing memory mechanisms expose nonlocal history but do not guarantee effective use, by recognizing that different layers prefer current, recent, or distant context. The method, combined with Cross‑Horizon Prediction Matching, achieves state‑of‑the‑art long‑range consistency on MemoBench and MovieBench while maintaining local continuity and incurring negligible inference overhead.
By Yixuan Ding, Jiahao Kong, Wei Huang, Ruijie Quan, Yi Yang
ResStreamGS introduces a residual‑sensitive dual‑stream framework for mobile volumetric video streaming that distinguishes temporally stable Gaussians from residual‑sensitive ones. Stable Gaussians are transmitted once per Group of Pictures, while only the residual‑sensitive Gaussians are included in the frame‑wise video stream, reducing bandwidth usage. Experiments on complex full‑scene videos show a 7.51–8.35 dB PSNR improvement over a V³‑style baseline, a payload reduction of up to 56.5%, and real‑time performance of 30.883 FPS on a Qualcomm Snapdragon 778G.
By Haoran Liu, Di Wu, Wang Luo, Hengyuan Na, Miao Hu, Guocong Quan
The paper introduces a 2D Gaussian Splatting pipeline that renders a dominant-eye RGB image and depth proxy, then reprojects and selectively patches the affiliated eye to reduce redundant work. By reusing alpha-blending weights and generating adaptive regions of interest, the method cuts sequential binocular rendering time by 15.5% to 28.8% and GPU memory by 6% to 11% on several datasets, with minimal quality loss. It demonstrates a practical efficiency‑quality trade‑off for static‑scene stereo rendering and suggests further evaluation on dynamic scenes and VR hardware.
By Hongfei Zhu, Ling Zhou
arXiv:2608.22465v1 Announce Type: new
Abstract: High-fidelity free-viewpoint video (FVV) and interactive rendering increasingly rely on explicit Gaussian representations, yet practical deployment rem...
By Xinhui Liu, Lei Liu, Zhenghao Chen, Lebin Zhou, Wei Wang, Wei Jiang