4 papers
IPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes
Yujia Liang, Jile Jiao, Xuetao Feng +3
Video Large Language Models (VideoLLMs) have demonstrated remarkable understanding capabilities, but are found struggling to tackle multi-shot scenarios,e.g., video clips with vary…
Training Matting Models without Alpha Labels
Wenze Liu, Zixuan Ye, Hao Lu +2
The labelling difficulty has been a longstanding problem in deep image matting. To escape from fine labels, this work explores using rough annotations such as trimaps coarsely indi…
SCAPE: A Simple and Strong Category-Agnostic Pose Estimator
Yujia Liang, Zixuan Ye, Wenze Liu +1
Category-Agnostic Pose Estimation (CAPE) aims to localize keypoints on an object of any category given few exemplars in an in-context manner. Prior arts involve sophisticated desig…
In-Context Matting
He Guo, Zixuan Ye, Zhiguo Cao +1
We introduce in-context matting, a novel task setting of image matting. Given a reference image of a certain foreground and guided priors such as points, scribbles, and masks, in-c…