4 accepted papers
With the malicious use and dissemination of multi-modal deepfake videos, researchers start to investigate multi-modal deepfake detection. Unfortunately, most of the existing methods tune all the parameters of the deep network with limited speech video datasets and are trained under coarse-grained co…
The recent advance in vision-language models is largely attributed to the abundance of image-text data. We aim to replicate this success for video-language models but there simply is not enough human-curated video-text data available. We thus resort to fine-tuning a video-language model from a stron…
We present a novel approach to robustly detect and perceive vehicles in different camera views as part of a cooperative vehicle-infrastructure system (CVIS). Our formulation is designed for arbitrary camera views and makes no assumptions about intrinsic or extrinsic parameters. First, to deal with m…
Holistically understanding an object with its 3D movable parts is essential for visual models of a robot to interact with the world. For example, only by understanding many possible part dynamics of other vehicles (e.g., door or trunk opening, taillight blinking for changing lane), a self-driving ve…