most citedOvarNet: Towards Open-vocabulary Object Attribute Recognition

5 citations · 12 across the 6 of their papers we have counts for

collaborators

6 papers

math.AP2023

Uniqueness of blowup at singular points for superconductivity problem

Lili Du, Xu Tang, Cong Wang

In this paper, we prove that the uniqueness of blowup at the maximum point of coincidence set of the superconductivity problem, mainly based on the Weiss-type and Monneau-type mono…

cs.CV20235 cited

Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances

Xiangrong Zhang, Tianyang Zhang, Guanchun Wang +4

Remote sensing object detection (RSOD), one of the most fundamental and challenging tasks in the remote sensing field, has received longstanding attention. In recent years, deep le…

cs.CV2023

MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation

Jie Guo, Qimeng Wang, Yan Gao +4

CLIP (Contrastive Language-Image Pretraining) is well-developed for open-vocabulary zero-shot image-level recognition, while its applications in pixel-level tasks are less investig…

cs.CV20232 cited

SoftMatch Distance: A Novel Distance for Weakly-Supervised Trend Change Detection in Bi-Temporal Images

Yuqun Yang, Xu Tang, Xiangrong Zhang +2

General change detection (GCD) and semantic change detection (SCD) are common methods for identifying changes and distinguishing object categories involved in those changes, respec…

cs.CV20235 cited

OvarNet: Towards Open-vocabulary Object Attribute Recognition

Keyan Chen, Xiaolong Jiang, Yao Hu +4

In this paper, we consider the problem of simultaneously detecting objects and inferring their visual attributes in an image, even for those with no manual annotations provided at…

cs.CV2021

SVIP: Sequence VerIfication for Procedures in Videos

Yicheng Qian, Weixin Luo, Dongze Lian +3

In this paper, we propose a novel sequence verification task that aims to distinguish positive video pairs performing the same action sequence from negative ones with step-level tr…