activity
20242026
collaborators

6 papers

cs.CV2026

SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM

Ming Nie, Dan Ding, Chunwei Wang +4

Large language models (LLMs) have demonstrated exceptional capabilities in text understanding, which has paved the way for their expansion into video LLMs (Vid-LLMs) to analyze vid…

cs.CV2025

VTimeCoT: Thinking by Drawing for Video Temporal Grounding and Reasoning

Jinglei Zhang, Yuanfan Guo, Rolandos Alexandros Potamias +3

In recent years, video question answering based on multimodal large language models (MLLM) has garnered considerable attention, due to the benefits from the substantial advancement…

cs.CV2025

GLaVE-Cap: Global-Local Aligned Video Captioning with Vision Expert Integration

Wan Xu, Feng Zhu, Yihan Zeng +4

Video detailed captioning aims to generate comprehensive video descriptions to facilitate video understanding. Recently, most efforts in the video detailed captioning community hav…

eess.IV2025

FreqPrior: Improving Video Diffusion Models with Frequency Filtering Gaussian Noise

Yunlong Yuan, Yuanfan Guo, Chunwei Wang +3

Text-driven video generation has advanced significantly due to developments in diffusion models. Beyond the training and sampling phases, recent studies have investigated noise pri…

cs.CV2025

Brick-Diffusion: Generating Long Videos with Brick-to-Wall Denoising

Yunlong Yuan, Yuanfan Guo, Chunwei Wang +2

Recent advances in diffusion models have greatly improved text-driven video generation. However, training models for long video generation demands significant computational power a…

cs.CV2024

EasyControl: Transfer ControlNet to Video Diffusion for Controllable Generation and Interpolation

Cong Wang, Jiaxi Gu, Panwen Hu +5

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. Ho…