works on

From the 1 of 17 linked papers with an AI index.

activity
20242026
collaborators

17 papers

cs.CV2026

CineWeaver: Training-Free Reference-Controllable Multi-Shot Long Video Generation for Cinematic Storytelling

Yuyang Huang, Yabo Chen, Wenrui Dai +6

CineWeaver introduces a training-free method that modifies pretrained video diffusion models to generate long, multi-shot cinematic videos with fine-grained reference control and c…

cs.CV2026

Disease-Centric Vision-Language Pretraining with Hybrid Visual Encoding for 3D Computed Tomography

Bowen Shi, Weiwei Cao, Ruifeng Yuan +5

Vision-language pre-training (VLP) holds great promise for general-purpose medical AI by leveraging radiology reports as rich textual supervision, yet existing methods struggle wit…

cs.LG2026

Information-Theoretic Optimization for Task-Adapted Compressed Sensing Magnetic Resonance Imaging

Xinyu Peng, Ziyang Zheng, Wenrui Dai +5

Task-adapted compressed sensing magnetic resonance imaging (CS-MRI) is emerging to address the specific demands of downstream clinical tasks with significantly fewer k-space measur…

cs.CV2026

Towards Holistic Modeling for Video Frame Interpolation with Auto-regressive Diffusion Transformers

Xinyu Peng, Han Li, Yuyang Huang +7

Existing video frame interpolation (VFI) methods often adopt a frame-centric approach, processing videos as independent short segments (e.g., triplets), which leads to temporal inc…

cs.CV2025

Error-Propagation-Free Learned Video Compression With Dual-Domain Progressive Temporal Alignment

Han Li, Shaohui Li, Wenrui Dai +5

Existing frameworks for learned video compression suffer from a dilemma between inaccurate temporal alignment and error propagation for motion estimation and compensation (ME/MC).…

cs.MM2025

EV-NVC: Efficient Variable bitrate Neural Video Compression

Yongcun Hu, Yingzhen Zhai, Jixiang Luo +4

Training neural video codec (NVC) with variable rate is a highly challenging task due to its complex training strategies and model structure. In this paper, we train an efficient v…