224 citations · 2.3k across the 117 of their papers we have counts for
119 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…
Recurrent Multi-scale Transformer for High-Resolution Salient Object Detection
Xinhao Deng, Pingping Zhang, Wei Liu +1
Salient Object Detection (SOD) aims to identify and segment the most conspicuous objects in an image or video. As an important pre-processing step, it has many potential applicatio…
CiteTracker: Correlating Image and Text for Visual Tracking
Xin Li, Yuqing Huang, Zhenyu He +3
Existing visual tracking methods typically take an image patch as the reference of the target to perform tracking. However, a single image patch cannot provide a complete and preci…
Exploring Lightweight Hierarchical Vision Transformers for Efficient Visual Tracking
Ben Kang, Xin Chen, Dong Wang +2
Transformer-based visual trackers have demonstrated significant progress owing to their superior modeling capabilities. However, existing trackers are hampered by low speed, limiti…
Towards Deeply Unified Depth-aware Panoptic Segmentation with Bi-directional Guidance Learning
Junwen He, Yifan Wang, Lijun Wang +6
Depth-aware panoptic segmentation is an emerging topic in computer vision which combines semantic and geometric understanding for more robust scene interpretation. Recent works pur…
Isomer: Isomerous Transformer for Zero-shot Video Object Segmentation
Yichen Yuan, Yifan Wang, Lijun Wang +5
Recent leading zero-shot video object segmentation (ZVOS) works devote to integrating appearance and motion information by elaborately designing feature fusion modules and identica…
Exploring Transformers for Open-world Instance Segmentation
Jiannan Wu, Yi Jiang, Bin Yan +3
Open-world instance segmentation is a rising task, which aims to segment all objects in the image by learning from a limited number of base-category objects. This task is challengi…
Video-based Person Re-identification with Long Short-Term Representation Learning
Xuehu Liu, Pingping Zhang, Huchuan Lu
Video-based person Re-Identification (V-ReID) aims to retrieve specific persons from raw videos captured by non-overlapped cameras. As a fundamental task, it spreads many multimedi…
UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory
Haiwen Diao, Bo Wan, Ying Zhang +3
Parameter-efficient transfer learning (PETL), i.e., fine-tuning a small portion of parameters, is an effective strategy for adapting pre-trained models to downstream domains. To fu…
Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking
Mingzhan Yang, Guangxin Han, Bin Yan +4
Multi-Object Tracking (MOT) aims to detect and associate all desired objects across frames. Most methods accomplish the task by explicitly or implicitly leveraging strong cues (i.e…
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…
ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary Transformer
Youwei Pang, Xiaoqi Zhao, Lihe Zhang +1
Deep learning (DL) has advanced the field of dense prediction, while gradually dissolving the inherent barriers between different tasks. However, most existing works focus on desig…
3rd Place Solution for PVUW2023 VSS Track: A Large Model for Semantic Segmentation on VSPW
Shijie Chang, Zeqi Hao, Ben Kang +6
In this paper, we introduce 3rd place solution for PVUW2023 VSS track. Semantic segmentation is a fundamental task in computer vision with numerous real-world applications. We have…
Neural Image Re-Exposure
Xinyu Zhang, Hefei Huang, Xu Jia +2
The shutter strategy applied to the photo-shooting process has a significant influence on the quality of the captured photograph. An improper shutter may lead to a blurry image, vi…
BEV-IO: Enhancing Bird's-Eye-View 3D Detection with Instance Occupancy
Zaibin Zhang, Yuanhang Zhang, Lijun Wang +2
A popular approach for constructing bird's-eye-view (BEV) representation in 3D detection is to lift 2D image features onto the viewing frustum space based on explicitly predicted d…
Deeply-Coupled Convolution-Transformer with Spatial-temporal Complementary Learning for Video-based Person Re-identification
Xuehu Liu, Chenyang Yu, Pingping Zhang +1
Advanced deep Convolutional Neural Networks (CNNs) have shown great success in video-based person Re-Identification (Re-ID). However, they usually focus on the most obvious regions…
MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation
Chongjian Ge, Junsong Chen, Enze Xie +5
Perception systems in modern autonomous driving vehicles typically take inputs from complementary multi-modal sensors, e.g., LiDAR and cameras. However, in real-world applications,…
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…
Visual Prompt Multi-Modal Tracking
Jiawen Zhu, Simiao Lai, Xin Chen +2
Visible-modal object tracking gives rise to a series of downstream multi-modal tracking tributaries. To inherit the powerful representations of the foundation model, a natural modu…
ARKitTrack: A New Diverse Dataset for Tracking Using Mobile RGB-D Data
Haojie Zhao, Junsong Chen, Lijun Wang +1
Compared with traditional RGB-only visual tracking, few datasets have been constructed for RGB-D tracking. In this paper, we propose ARKitTrack, a new RGB-D tracking dataset for bo…
GM-NeRF: Learning Generalizable Model-based Neural Radiance Fields from Multi-view Images
Jianchuan Chen, Wentao Yi, Liqian Ma +2
In this work, we focus on synthesizing high-fidelity novel view images for arbitrary human performers, given a set of sparse multi-view images. It is a challenging task due to the…
Plug-and-Play Regulators for Image-Text Matching
Haiwen Diao, Ying Zhang, Wei Liu +2
Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching. Generally, recent approaches first employ a cross-modal atte…
Dual Memory Aggregation Network for Event-Based Object Detection with Learnable Representation
Dongsheng Wang, Xu Jia, Yang Zhang +5
Event-based cameras are bio-inspired sensors that capture brightness change of every pixel in an asynchronous manner. Compared with frame-based sensors, event cameras have microsec…
MSNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation
Xiaoqi Zhao, Hongpeng Jia, Youwei Pang +5
Accurate medical image segmentation is critical for early medical diagnosis. Most existing methods are based on U-shape structure and use element-wise addition or concatenation to…