79 citations · 92 across the 5 of their papers we have counts for
6 papers
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…
Towards Open Vocabulary Learning: A Survey
Jianzong Wu, Xiangtai Li, Shilin Xu +9
In the field of visual scene understanding, deep neural networks have made impressive advancements in various core tasks like segmentation, tracking, and detection. However, most a…
GRES: Generalized Referring Expression Segmentation
Chang Liu, Henghui Ding, Xudong Jiang
Referring Expression Segmentation (RES) aims to generate a segmentation mask for the object described by a given language expression. Existing classic RES datasets and methods comm…
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…
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…