219 citations · 831 across the 34 of their papers we have counts for
34 papers
State Space Model for New-Generation Network Alternative to Transformers: A Survey
Xiao Wang, Shiao Wang, Yuhe Ding +13
In the post-deep learning era, the Transformer architecture has demonstrated its powerful performance across pre-trained big models and various downstream tasks. However, the enorm…
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…
Unsupervised Domain Adaptation via Distilled Discriminative Clustering
Hui Tang, Yaowei Wang, Kui Jia
Unsupervised domain adaptation addresses the problem of classifying data in an unlabeled target domain, given labeled source domain data that share a common label space but follow…
Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey
Xiao Wang, Guangyao Chen, Guangwu Qian +5
With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as BERT, ViT, GPT, etc. Inspired by the success of these models in single domains…
Universal Object Detection with Large Vision Model
Feng Lin, Wenze Hu, Yaowei Wang +5
Over the past few years, there has been growing interest in developing a broad, universal, and general-purpose computer vision system. Such systems have the potential to address a…
HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors
Xiao Wang, Zongzhen Wu, Bo Jiang +5
The main streams of human activity recognition (HAR) algorithms are developed based on RGB cameras which are suffered from illumination, fast motion, privacy-preserving, and large…
Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric
Chuanming Tang, Xiao Wang, Ju Huang +5
Combining the Color and Event cameras (also called Dynamic Vision Sensors, DVS) for robust object tracking is a newly emerging research topic in recent years. Existing color-event…
Spikformer: When Spiking Neural Network Meets Transformer
Zhaokun Zhou, Yuesheng Zhu, Chao He +4
We consider two biologically plausible structures, the Spiking Neural Network (SNN) and the self-attention mechanism. The former offers an energy-efficient and event-driven paradig…
Prompt-based Learning for Unpaired Image Captioning
Peipei Zhu, Xiao Wang, Lin Zhu +4
Unpaired Image Captioning (UIC) has been developed to learn image descriptions from unaligned vision-language sample pairs. Existing works usually tackle this task using adversaria…
Global-Supervised Contrastive Loss and View-Aware-Based Post-Processing for Vehicle Re-Identification
Zhijun Hu, Yong Xu, Jie Wen +4
In this paper, we propose a Global-Supervised Contrastive loss and a view-aware-based post-processing (VABPP) method for the field of vehicle re-identification. The traditional sup…
Fine-Grained Object Classification via Self-Supervised Pose Alignment
Xuhui Yang, Yaowei Wang, Ke Chen +2
Semantic patterns of fine-grained objects are determined by subtle appearance difference of local parts, which thus inspires a number of part-based methods. However, due to uncontr…
Peng Cheng Object Detection Benchmark for Smart City
Yaowei Wang, Zhouxin Yang, Rui Liu +4
Object detection is an algorithm that recognizes and locates the objects in the image and has a wide range of applications in the visual understanding of complex urban scenes. Exis…
Boosting Crowd Counting via Multifaceted Attention
Hui Lin, Zhiheng Ma, Rongrong Ji +2
This paper focuses on the challenging crowd counting task. As large-scale variations often exist within crowd images, neither fixed-size convolution kernel of CNN nor fixed-size at…
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…