95 citations · 218 across the 23 of their papers we have counts for
8 papers · 2 filters
VGSG: Vision-Guided Semantic-Group Network for Text-based Person Search
Shuting He, Hao Luo, Wei Jiang +2
Text-based Person Search (TBPS) aims to retrieve images of target pedestrian indicated by textual descriptions. It is essential for TBPS to extract fine-grained local features and…
Region Generation and Assessment Network for Occluded Person Re-Identification
Shuting He, Weihua Chen, Kai Wang +4
Person Re-identification (ReID) plays a more and more crucial role in recent years with a wide range of applications. Existing ReID methods are suffering from the challenges of mis…
MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions
Henghui Ding, Chang Liu, Shuting He +2
This paper strives for motion expressions guided video segmentation, which focuses on segmenting objects in video content based on a sentence describing the motion of the objects.…
GREC: Generalized Referring Expression Comprehension
Shuting He, Henghui Ding, Chang Liu +1
The objective of Classic Referring Expression Comprehension (REC) is to produce a bounding box corresponding to the object mentioned in a given textual description. Commonly, exist…
Primitive Generation and Semantic-related Alignment for Universal Zero-Shot Segmentation
Shuting He, Henghui Ding, Wei Jiang
We study universal zero-shot segmentation in this work to achieve panoptic, instance, and semantic segmentation for novel categories without any training samples. Such zero-shot se…
Prototype Adaption and Projection for Few- and Zero-shot 3D Point Cloud Semantic Segmentation
Shuting He, Xudong Jiang, Wei Jiang +1
In this work, we address the challenging task of few-shot and zero-shot 3D point cloud semantic segmentation. The success of few-shot semantic segmentation in 2D computer vision is…
Semantic-Promoted Debiasing and Background Disambiguation for Zero-Shot Instance Segmentation
Shuting He, Henghui Ding, Wei Jiang
Zero-shot instance segmentation aims to detect and precisely segment objects of unseen categories without any training samples. Since the model is trained on seen categories, there…
MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
Henghui Ding, Chang Liu, Shuting He +3
Video object segmentation (VOS) aims at segmenting a particular object throughout the entire video clip sequence. The state-of-the-art VOS methods have achieved excellent performan…