arXiv:2611.05359v2 Announce Type: replace
Abstract: This paper presents GSCV++, a lightweight pipeline for 3D {G}aussian {S}platting (GS) sequences {C}ompression with standard {V}ideo codecs. To meet...
By Qi Yang, Yingzhan Xu, Kai Zhang, Li Zhang
The paper introduces Quality-Constrained Image Coding for Machines (ICM), which compresses images by treating a computer vision application as the primary observer while limiting human-observed quality to a specified target. By formulating joint compression and segmentation as a constrained optimization problem, the authors design penalty functions that steer the codec toward the desired visual quality, allowing remaining coding capacity to enhance machine performance. Experiments demonstrate significant bitrate savings—up to 22.82% over unconstrained joint optimization and 29.81% over a simple rate–distortion baseline—while maintaining target visual quality without added complexity.
By Khoa Pham-Dinh, Sanaz Nami, Hamed Rezazadegan Tavakoli, Moncef Gabbouj, Farhad Pakdaman
arXiv:2603.17546v2 Announce Type: replace
Abstract: Perceptual video compression leverages generative priors to reconstruct realistic textures and motions at low bitrates. However, existing perceptua...
By Daowen Li, Ruixiao Dong, Kai Li, Ying Chen, Ding Ding, Li Li
arXiv:2608.28429v1 Announce Type: new
Abstract: Event cameras generate asynchronous, sparse data streams with microsecond temporal resolution, but in moderate-to-high motion scenes they can produce a...
By Zahra Rezaee, Catarina Brites, Jo\~ao Ascenso
arXiv:2610.17412v1 Announce Type: cross
Abstract: Vision Transformers incur high computational costs when processing long visual token sequences. Existing reduction methods typically rank tokens inde...
By Xiaoya Tang, Shilong Liu, Daniel Smolyak, Xiwen Li, Quynh Nguyen, Tolga Tasdizen
arXiv:2512. 08240v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) rely on hundreds of visual tokens, leading to high computational and memory costs.
By Jusheng Zhang, Xiaoyang Guo, Tongyu Mo, Qinhan Lv, Wenhao Chai, Jian Wang, Keze Wang, Liang Lin