26 citations · 29 across the 10 of their papers we have counts for
11 papers
Linear Scaling Video VLMs for Long Video Understanding
Cristobal Eyzaguirre, Jiajun Wu, Juan Carlos Niebles
Video vision-language models (VLMs) are increasingly used in long-horizon and streaming settings, yet most video encoders still rely on spatiotemporal self-attention, causing compu…
Autoregressive Flow Matching for Motion Prediction
Johnathan Xie, Stefan Stojanov, Cristobal Eyzaguirre +2
Motion prediction has been studied in different contexts with models trained on narrow distributions and applied to downstream tasks in human motion prediction and robotics. Simult…
Taming generative video models for zero-shot optical flow extraction
Seungwoo Kim, Khai Loong Aw, Klemen Kotar +8
Extracting optical flow from videos remains a core computer vision problem. Motivated by the recent success of large general-purpose models, we ask whether frozen self-supervised v…
Understanding Complexity in VideoQA via Visual Program Generation
Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave +5
We propose a data-driven approach to analyzing query complexity in Video Question Answering (VideoQA). Previous efforts in benchmark design have relied on human expertise to design…
T*: Re-thinking Temporal Search for Long-Form Video Understanding
Jinhui Ye, Zihan Wang, Haosen Sun +9
Efficiently understanding long-form videos remains a significant challenge in computer vision. In this work, we revisit temporal search paradigms for long-form video understanding…
Streaming Detection of Queried Event Start
Cristobal Eyzaguirre, Eric Tang, Shyamal Buch +3
Robotics, autonomous driving, augmented reality, and many embodied computer vision applications must quickly react to user-defined events unfolding in real time. We address this se…