295 citations · 403 across the 11 of their papers we have counts for
11 papers
Generative Prompt Model for Weakly Supervised Object Localization
Yuzhong Zhao, Qixiang Ye, Weijia Wu +2
Weakly supervised object localization (WSOL) remains challenging when learning object localization models from image category labels. Conventional methods that discriminatively tra…
Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection
Feng Liu, Xiaosong Zhang, Zhiliang Peng +4
Modern object detectors have taken the advantages of backbone networks pre-trained on large scale datasets. Except for the backbone networks, however, other components such as the…
Multiple instance active learning for object detection
Tianning Yuan, Fang Wan, Mengying Fu +4
Despite the substantial progress of active learning for image recognition, there still lacks an instance-level active learning method specified for object detection. In this paper,…
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…
Domain Contrast for Domain Adaptive Object Detection
Feng Liu, Xiaoxong Zhang, Fang Wan +2
We present Domain Contrast (DC), a simple yet effective approach inspired by contrastive learning for training domain adaptive detectors. DC is deduced from the error bound minimiz…
Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning
Zhekun Luo, Devin Guillory, Baifeng Shi +4
Weakly-supervised action localization requires training a model to localize the action segments in the video given only video level action label. It can be solved under the Multipl…
FreeAnchor: Learning to Match Anchors for Visual Object Detection
Xiaosong Zhang, Fang Wan, Chang Liu +2
Modern CNN-based object detectors assign anchors for ground-truth objects under the restriction of object-anchor Intersection-over-Unit (IoU). In this study, we propose a learning-…
Utilizing the Instability in Weakly Supervised Object Detection
Yan Gao, Boxiao Liu, Nan Guo +4
Weakly supervised object detection (WSOD) focuses on training object detector with only image-level annotations, and is challenging due to the gap between the supervision and the o…
C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection
Fang Wan, Chang Liu, Wei Ke +3
Weakly supervised object detection (WSOD) is a challenging task when provided with image category supervision but required to simultaneously learn object locations and object detec…
Min-Entropy Latent Model for Weakly Supervised Object Detection
Fang Wan, Pengxu Wei, Zhenjun Han +2
Weakly supervised object detection is a challenging task when provided with image category supervision but required to learn, at the same time, object locations and object detector…
SIXray : A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images
Caijing Miao, Lingxi Xie, Fang Wan +4
In this paper, we present a large-scale dataset and establish a baseline for prohibited item discovery in Security Inspection X-ray images. Our dataset, named SIXray, consists of 1…