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cs.CV2026

Bridging Event Streams and DiT: Event-Guided Video Frame Interpolation

Guixu Lin, Yuyang Yu, Xiang Ji +6

Latent diffusion models have recently advanced video frame interpolation by synthesizing intermediate frames between input images. However, handling large temporal gaps and complex…

cs.CV2026

Moment-Reenacting: Inverse Motion Degradation with Cross-shutter Guidance

Xiang Ji, Guixu Lin, Zhengwei Yin +2

Motion degradation, manifested as blur in global shutter (GS) images or rolling shutter (RS) distortion in RS counterparts, remains a fundamental challenge in computational imaging…

cs.CV2025

Tree-NeRV: A Tree-Structured Neural Representation for Efficient Non-Uniform Video Encoding

Jiancheng Zhao, Yifan Zhan, Qingtian Zhu +5

Implicit Neural Representations for Videos (NeRV) have emerged as a powerful paradigm for video representation, enabling direct mappings from frame indices to video frames. However…

cs.CV2025

All-in-One Transferring Image Compression from Human Perception to Multi-Machine Perception

Jiancheng Zhao, Xiang Ji, Yinqiang Zheng

Efficiently transferring Learned Image Compression (LIC) model from human perception to machine perception is an emerging challenge in vision-centric representation learning. Exist…

cs.CV2024

RS-NeRF: Neural Radiance Fields from Rolling Shutter Images

Muyao Niu, Tong Chen, Yifan Zhan +3

Neural Radiance Fields (NeRFs) have become increasingly popular because of their impressive ability for novel view synthesis. However, their effectiveness is hindered by the Rollin…

cs.CV2024

Motion Blur Decomposition with Cross-shutter Guidance

Xiang Ji, Haiyang Jiang, Yinqiang Zheng

Motion blur is a frequently observed image artifact, especially under insufficient illumination where exposure time has to be prolonged so as to collect more photons for a bright e…