219 citations · 831 across the 34 of their papers we have counts for
13 papers · 1 filter
An Informative Tracking Benchmark
Xin Li, Qiao Liu, Wenjie Pei +4
Along with the rapid progress of visual tracking, existing benchmarks become less informative due to redundancy of samples and weak discrimination between current trackers, making…
Learning to Share in Multi-Agent Reinforcement Learning
Yuxuan Yi, Ge Li, Yaowei Wang +1
In this paper, we study the problem of networked multi-agent reinforcement learning (MARL), where a number of agents are deployed as a partially connected network and each interact…
Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection
Rui Liu, Yahong Han, Yaowei Wang +1
Domain adaptive object detection (DAOD) aims to improve the generalization ability of detectors when the training and test data are from different domains. Considering the signific…
VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows
Xiao Wang, Jianing Li, Lin Zhu +6
Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lo…
Direct Measure Matching for Crowd Counting
Hui Lin, Xiaopeng Hong, Zhiheng Ma +4
Traditional crowd counting approaches usually use Gaussian assumption to generate pseudo density ground truth, which suffers from problems like inaccurate estimation of the Gaussia…
MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking
Xiao Wang, Xiujun Shu, Shiliang Zhang +4
Many RGB-T trackers attempt to attain robust feature representation by utilizing an adaptive weighting scheme (or attention mechanism). Different from these works, we propose a new…
Tracking by Joint Local and Global Search: A Target-aware Attention based Approach
Xiao Wang, Jin Tang, Bin Luo +3
Tracking-by-detection is a very popular framework for single object tracking which attempts to search the target object within a local search window for each frame. Although such l…
Conformer: Local Features Coupling Global Representations for Visual Recognition
Zhiliang Peng, Wei Huang, Shanzhi Gu +4
Within Convolutional Neural Network (CNN), the convolution operations are good at extracting local features but experience difficulty to capture global representations. Within visu…
PanGu-: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation
Wei Zeng, Xiaozhe Ren, Teng Su +35
Large-scale Pretrained Language Models (PLMs) have become the new paradigm for Natural Language Processing (NLP). PLMs with hundreds of billions parameters such as GPT-3 have demon…
Contrastive Neural Architecture Search with Neural Architecture Comparators
Yaofo Chen, Yong Guo, Qi Chen +4
One of the key steps in Neural Architecture Search (NAS) is to estimate the performance of candidate architectures. Existing methods either directly use the validation performance…
AAformer: Auto-Aligned Transformer for Person Re-Identification
Kuan Zhu, Haiyun Guo, Shiliang Zhang +4
In person re-identification (re-ID), extracting part-level features from person images has been verified to be crucial to offer fine-grained information. Most of the existing CNN-b…
Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark
Xiao Wang, Xiujun Shu, Zhipeng Zhang +4
Tracking by natural language specification is a new rising research topic that aims at locating the target object in the video sequence based on its language description. Compared…
Dynamic Attention guided Multi-Trajectory Analysis for Single Object Tracking
Xiao Wang, Zhe Chen, Jin Tang +4
Most of the existing single object trackers track the target in a unitary local search window, making them particularly vulnerable to challenging factors such as heavy occlusions a…