13 papers · 1 filter
UVE: Are MLLMs Unified Evaluators for AI-Generated Videos?
Yuanxin Liu, Rui Zhu, Shuhuai Ren +4
With the rapid growth of video generative models (VGMs), it is essential to develop reliable and comprehensive automatic metrics for AI-generated videos (AIGVs). Existing methods e…
TEMPLE: Incentivizing Temporal Understanding of Video Large Language Models via Progressive Pre-SFT Alignment
Shicheng Li, Lei Li, Kun Ouyang +7
Video Large Language Models (Video LLMs) have achieved significant success by adopting the paradigm of large-scale pre-training followed by supervised fine-tuning (SFT). However, e…
Generative Frame Sampler for Long Video Understanding
Linli Yao, Haoning Wu, Kun Ouyang +5
Despite recent advances in Video Large Language Models (VideoLLMs), effectively understanding long-form videos remains a significant challenge. Perceiving lengthy videos containing…
PunchBench: Benchmarking MLLMs in Multimodal Punchline Comprehension
Kun Ouyang, Yuanxin Liu, Shicheng Li +5
Multimodal punchlines, which involve humor or sarcasm conveyed in image-caption pairs, are a popular way of communication on online multimedia platforms. With the rapid development…
RICO: Improving Accuracy and Completeness in Image Recaptioning via Visual Reconstruction
Yuchi Wang, Yishuo Cai, Shuhuai Ren +6
Image recaptioning is widely used to generate training datasets with enhanced quality for various multimodal tasks. Existing recaptioning methods typically rely on powerful multimo…
TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming Videos
Linli Yao, Yicheng Li, Yuancheng Wei +11
The rapid growth of online video platforms, particularly live streaming services, has created an urgent need for real-time video understanding systems. These systems must process c…