116 citations · 188 across the 11 of their papers we have counts for
11 papers · 1 filter
Mitigating Hallucination in Visual Language Models with Visual Supervision
Zhiyang Chen, Yousong Zhu, Yufei Zhan +4
Large vision-language models (LVLMs) suffer from hallucination a lot, generating responses that apparently contradict to the image content occasionally. The key problem lies in its…
ZBS: Zero-shot Background Subtraction via Instance-level Background Modeling and Foreground Selection
Yongqi An, Xu Zhao, Tao Yu +4
Background subtraction (BGS) aims to extract all moving objects in the video frames to obtain binary foreground segmentation masks. Deep learning has been widely used in this field…
Efficient Masked Autoencoders with Self-Consistency
Zhaowen Li, Yousong Zhu, Zhiyang Chen +5
Inspired by the masked language modeling (MLM) in natural language processing tasks, the masked image modeling (MIM) has been recognized as a strong self-supervised pre-training me…
Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks
Zhiyang Chen, Yousong Zhu, Zhaowen Li +8
Visual tasks vary a lot in their output formats and concerned contents, therefore it is hard to process them with an identical structure. One main obstacle lies in the high-dimensi…
Transfering Low-Frequency Features for Domain Adaptation
Zhaowen Li, Xu Zhao, Chaoyang Zhao +2
Previous unsupervised domain adaptation methods did not handle the cross-domain problem from the perspective of frequency for computer vision. The images or feature maps of differe…
UniVIP: A Unified Framework for Self-Supervised Visual Pre-training
Zhaowen Li, Yousong Zhu, Fan Yang +9
Self-supervised learning (SSL) holds promise in leveraging large amounts of unlabeled data. However, the success of popular SSL methods has limited on single-centric-object images…
Pruning-aware Sparse Regularization for Network Pruning
Nanfei Jiang, Xu Zhao, Chaoyang Zhao +3
Structural neural network pruning aims to remove the redundant channels in the deep convolutional neural networks (CNNs) by pruning the filters of less importance to the final outp…
DPT: Deformable Patch-based Transformer for Visual Recognition
Zhiyang Chen, Yousong Zhu, Chaoyang Zhao +4
Transformer has achieved great success in computer vision, while how to split patches in an image remains a problem. Existing methods usually use a fixed-size patch embedding which…
MST: Masked Self-Supervised Transformer for Visual Representation
Zhaowen Li, Zhiyang Chen, Fan Yang +8
Transformer has been widely used for self-supervised pre-training in Natural Language Processing (NLP) and achieved great success. However, it has not been fully explored in visual…
Adaptive Class Suppression Loss for Long-Tail Object Detection
Tong Wang, Yousong Zhu, Chaoyang Zhao +3
To address the problem of long-tail distribution for the large vocabulary object detection task, existing methods usually divide the whole categories into several groups and treat…
CoupleNet: Coupling Global Structure with Local Parts for Object Detection
Yousong Zhu, Chaoyang Zhao, Jinqiao Wang +3
The region-based Convolutional Neural Network (CNN) detectors such as Faster R-CNN or R-FCN have already shown promising results for object detection by combining the region propos…