Hugging Face Trending Papers
Aug 19

CamWorldQA: Perceptual Quality Assessment of Camera-Controlled World Video Generation

CamWorldQA introduces the first benchmark for assessing the perceptual quality of camera‑controlled world video generation, featuring 720 videos generated by six methods from 20 source videos across six camera trajectories, each scored by human raters. The paper also presents CWQA, a no‑reference quality assessment network that combines spatial, temporal motion, and optical flow features to predict quality scores. Experiments show CWQA outperforms existing VQA methods on the CamWorldQA dataset.

arXiv Computer Vision
Sep 7

Scalable Neural Video Representation Compression

Scalable Neural Video Representation Compression (S-NVRC) introduces a scalable implicit neural representation (INR) video codec that supports fine-grained bitrate and decoding‑complexity scalability from a single embedded bitstream. It uses a coarse‑to‑fine prefix for feature grids and a nested prefix for network layers, enabling a wide range of operating points while maintaining a single encoding. On the UVG dataset, S‑NVRC outperforms SHM 12.4 and multi‑layer VTM‑20.0 by 43.7 % and 5.6 % in BD‑rate, respectively, and offers flexible complexity scalability.

By Tianhao Peng, Ho Man Kwan, Fan Zhang, Shan Liu, David Bull
arXiv AI
Sep 3

VoRTeC: Taming Foundation Flow for One-step Real time Video Compression

The paper introduces VoRTeC, a video compression framework that leverages a foundational flow model to encode latent video representations compactly and predict their positions along flow trajectories. By integrating multi‑scale priors and avoiding access to flow‑matching network parameters, VoRTeC achieves one‑step decoding with high perceptual fidelity, while maintaining temporal consistency through tail‑frame reuse and prior caching. Experiments show a 58% reduction in bit consumption compared to prior diffusion‑based methods and a decoding speed increase ranging from 3 to 197 times, reaching 13 FPS at 720p and 32 FPS at 480p.

By Yichong Xia, Qinhong Wu, Qinhong Wu, Jinpeng Wang, Zeyuan Chen, Haoqian Wang
arXiv Computer Vision
Sep 23

COVER: Codec-Robust Video Watermarking with Generative Video Priors

COVER is a new video watermarking method that targets codec compression as its primary design goal. It embeds the watermark payload in the latent space of a frozen generative video autoencoder and recovers it by re‑encoding the received video into the same latent space. Using a differentiable codec surrogate bank, COVER achieves high bit accuracy across multiple codecs while keeping marked videos visually close to the originals.

By Yuxin Cao, Hao Yang, Ziqi Ding, Jie Hao, Wei Song