6 citations · 13 across the 8 of their papers we have counts for
8 papers
Beyond One-to-One: Rethinking the Referring Image Segmentation
Yutao Hu, Qixiong Wang, Wenqi Shao +4
Referring image segmentation aims to segment the target object referred by a natural language expression. However, previous methods rely on the strong assumption that one sentence…
Dense Affinity Matching for Few-Shot Segmentation
Hao Chen, Yonghan Dong, Zheming Lu +4
Few-Shot Segmentation (FSS) aims to segment the novel class images with a few annotated samples. In this paper, we propose a dense affinity matching (DAM) framework to exploit the…
SegGPT Meets Co-Saliency Scene
Yi Liu, Shoukun Xu, Dingwen Zhang +1
Co-salient object detection targets at detecting co-existed salient objects among a group of images. Recently, a generalist model for segmenting everything in context, called SegGP…
MAPLE: Masked Pseudo-Labeling autoEncoder for Semi-supervised Point Cloud Action Recognition
Xiaodong Chen, Wu Liu, Xinchen Liu +3
Recognizing human actions from point cloud videos has attracted tremendous attention from both academia and industry due to its wide applications like automatic driving, robotics,…
Boosting Video-Text Retrieval with Explicit High-Level Semantics
Haoran Wang, Di Xu, Dongliang He +4
Video-text retrieval (VTR) is an attractive yet challenging task for multi-modal understanding, which aims to search for relevant video (text) given a query (video). Existing metho…
Temporal Saliency Query Network for Efficient Video Recognition
Boyang Xia, Zhihao Wang, Wenhao Wu +2
Efficient video recognition is a hot-spot research topic with the explosive growth of multimedia data on the Internet and mobile devices. Most existing methods select the salient f…