5 papers
PercepCap: Video Captioner with Structured Spatio-Temporal Perception
Yifan Xu, Zihao Wang, Zhixiao Wang +6
Video captioning requires fine-grained spatio-temporal understanding of videos, including spatial perception of where objects are located and temporal perception of when events occ…
MotionEnhancer: Leveraging Video Diffusion for Motion-Enhanced Vision-Language Models
Yifan Xu, Chao Zhang, Ruifei Ma +4
The new era has witnessed a remarkable capability to extend Vision-Language Models (VLMs) for tackling tasks of video understanding. While current VLMs excel at event- or story-lev…
WISER: Wider Search, Deeper Thinking, and Adaptive Fusion for Training-Free Zero-Shot Composed Image Retrieval
Tianyue Wang, Leigang Qu, Tianyu Yang +4
Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve target images given a multimodal query (comprising a reference image and a modification text), without training on anno…
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Desen Meng, Rui Huang, Zhilin Dai +8
While recent advances in reinforcement learning have significantly enhanced reasoning capabilities in large language models (LLMs), these techniques remain underexplored in multi-m…
CaReBench: A Fine-Grained Benchmark for Video Captioning and Retrieval
Yifan Xu, Xinhao Li, Yichun Yang +3
Video understanding, including video captioning and retrieval, is still a great challenge for video-language models (VLMs). The existing video retrieval and caption benchmarks only…