1 citations · 2 across the 6 of their papers we have counts for
9 papers · 1 filter
Incentivizing Temporal-Awareness in Egocentric Video Understanding Models
Zhiyang Xu, Tian Qin, Bowen Jin +4
Multimodal large language models (MLLMs) have recently shown strong performance in visual understanding, yet they often lack temporal awareness, particularly in egocentric settings…
Breaking Down Video LLM Benchmarks: Knowledge, Spatial Perception, or True Temporal Understanding?
Bo Feng, Zhengfeng Lai, Shiyu Li +4
Existing video understanding benchmarks often conflate knowledge-based and purely image-based questions, rather than clearly isolating a model's temporal reasoning ability, which i…
StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant
Haibo Wang, Bo Feng, Zhengfeng Lai +6
We present StreamBridge, a simple yet effective framework that seamlessly transforms offline Video-LLMs into streaming-capable models. It addresses two fundamental challenges in ad…
SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understanding
Mingze Xu, Mingfei Gao, Shiyu Li +7
We introduce SlowFast-LLaVA-1.5 (abbreviated as SF-LLaVA-1.5), a family of video large language models (LLMs) offering a token-efficient solution for long-form video understanding.…
ETVA: Evaluation of Text-to-Video Alignment via Fine-grained Question Generation and Answering
Kaisi Guan, Zhengfeng Lai, Yuchong Sun +5
Precisely evaluating semantic alignment between text prompts and generated videos remains a challenge in Text-to-Video (T2V) Generation. Existing text-to-video alignment metrics li…
STIV: Scalable Text and Image Conditioned Video Generation
Zongyu Lin, Wei Liu, Chen Chen +13
The field of video generation has made remarkable advancements, yet there remains a pressing need for a clear, systematic recipe that can guide the development of robust and scalab…