49 citations · 188 across the 17 of their papers we have counts for
19 papers
A Mutual Learning Method for Salient Object Detection with intertwined Multi-Supervision--Revised
Runmin Wu, Mengyang Feng, Wenlong Guan +3
Though deep learning techniques have made great progress in salient object detection recently, the predicted saliency maps still suffer from incomplete predictions due to the inter…
Other Tokens Matter: Exploring Global and Local Features of Vision Transformers for Object Re-Identification
Yingquan Wang, Pingping Zhang, Dong Wang +1
Object Re-Identification (Re-ID) aims to identify and retrieve specific objects from images captured at different places and times. Recently, object Re-ID has achieved great succes…
Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters
Jiazuo Yu, Yunzhi Zhuge, Lu Zhang +4
Continual learning can empower vision-language models to continuously acquire new knowledge, without the need for access to the entire historical dataset. However, mitigating the p…
Tracking Anything in High Quality
Jiawen Zhu, Zhenyu Chen, Zeqi Hao +9
Visual object tracking is a fundamental video task in computer vision. Recently, the notably increasing power of perception algorithms allows the unification of single/multiobject…
Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
Xin Chen, Ben Kang, Jiawen Zhu +3
In this paper, we introduce a new sequence-to-sequence learning framework for RGB-based and multi-modal object tracking. First, we present SeqTrack for RGB-based tracking. It casts…
Video Annotation for Visual Tracking via Selection and Refinement
Kenan Dai, Jie Zhao, Lijun Wang +5
Deep learning based visual trackers entail offline pre-training on large volumes of video datasets with accurate bounding box annotations that are labor-expensive to achieve. We pr…