147 citations · 232 across the 9 of their papers we have counts for
9 papers
SIOD: Single Instance Annotated Per Category Per Image for Object Detection
Hanjun Li, Xingjia Pan, Ke Yan +2
Object detection under imperfect data receives great attention recently. Weakly supervised object detection (WSOD) suffers from severe localization issues due to the lack of instan…
SeqTR: A Simple yet Universal Network for Visual Grounding
Chaoyang Zhu, Yiyi Zhou, Yunhang Shen +7
In this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e.g., phrase localization, referring expression comprehension (REC) and segmentati…
Expanding Low-Density Latent Regions for Open-Set Object Detection
Jiaming Han, Yuqiang Ren, Jian Ding +3
Modern object detectors have achieved impressive progress under the close-set setup. However, open-set object detection (OSOD) remains challenging since objects of unknown categori…
CrossRectify: Leveraging Disagreement for Semi-supervised Object Detection
Chengcheng Ma, Xingjia Pan, Qixiang Ye +3
Semi-supervised object detection has recently achieved substantial progress. As a mainstream solution, the self-labeling-based methods train the detector on both labeled data and u…
Distributed Attention for Grounded Image Captioning
Nenglun Chen, Xingjia Pan, Runnan Chen +7
We study the problem of weakly supervised grounded image captioning. That is, given an image, the goal is to automatically generate a sentence describing the context of the image w…
StyTr: Image Style Transfer with Transformers
Yingying Deng, Fan Tang, Weiming Dong +4
The goal of image style transfer is to render an image with artistic features guided by a style reference while maintaining the original content. Owing to the locality in convoluti…
Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization
Xingjia Pan, Yingguo Gao, Zhiwen Lin +5
Weakly supervised object localization(WSOL) remains an open problem given the deficiency of finding object extent information using a classification network. Although prior works s…
TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization
Wei Gao, Fang Wan, Xingjia Pan +5
Weakly supervised object localization (WSOL) is a challenging problem when given image category labels but requires to learn object localization models. Optimizing a convolutional…
Dynamic Refinement Network for Oriented and Densely Packed Object Detection
Xingjia Pan, Yuqiang Ren, Kekai Sheng +5
Object detection has achieved remarkable progress in the past decade. However, the detection of oriented and densely packed objects remains challenging because of following inheren…