21 citations · 62 across the 14 of their papers we have counts for
14 papers
Improving the Multi-label Atomic Activity Recognition by Robust Visual Feature and Advanced Attention @ ROAD++ Atomic Activity Recognition 2024
Jiamin Cao, Lingqi Wang, Kexin Zhang +3
Road++ Track3 proposes a multi-label atomic activity recognition task in traffic scenarios, which can be standardized as a 64-class multi-label video action recognition task. In th…
Heterogeneous Network Based Contrastive Learning Method for PolSAR Land Cover Classification
Jianfeng Cai, Yue Ma, Zhixi Feng +1
Polarimetric synthetic aperture radar (PolSAR) image interpretation is widely used in various fields. Recently, deep learning has made significant progress in PolSAR image classifi…
Geometric Prior Guided Feature Representation Learning for Long-Tailed Classification
Yanbiao Ma, Licheng Jiao, Fang Liu +3
Real-world data are long-tailed, the lack of tail samples leads to a significant limitation in the generalization ability of the model. Although numerous approaches of class re-bal…
Changes-Aware Transformer: Learning Generalized Changes Representation
Dan Wang, Licheng Jiao, Jie Chen +2
Difference features obtained by comparing the images of two periods play an indispensable role in the change detection (CD) task. However, a pair of bi-temporal images can exhibit…
Multi-model fusion for Aerial Vision and Dialog Navigation based on human attention aids
Xinyi Wang, Xuan Cui, Danxu Li +2
Drones have been widely used in many areas of our daily lives. It relieves people of the burden of holding a controller all the time and makes drone control easier to use for peopl…
DiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model
Xiangrong Zhang, Shunli Tian, Guanchun Wang +2
Hyperspectral image change detection (HSI-CD) has emerged as a crucial research area in remote sensing due to its ability to detect subtle changes on the earth's surface. Recently,…
SoftMatch Distance: A Novel Distance for Weakly-Supervised Trend Change Detection in Bi-Temporal Images
Yuqun Yang, Xu Tang, Xiangrong Zhang +2
General change detection (GCD) and semantic change detection (SCD) are common methods for identifying changes and distinguishing object categories involved in those changes, respec…
Predicting and Enhancing the Fairness of DNNs with the Curvature of Perceptual Manifolds
Yanbiao Ma, Licheng Jiao, Fang Liu +6
To address the challenges of long-tailed classification, researchers have proposed several approaches to reduce model bias, most of which assume that classes with few samples are w…
Delving into Semantic Scale Imbalance
Yanbiao Ma, Licheng Jiao, Fang Liu +3
Model bias triggered by long-tailed data has been widely studied. However, measure based on the number of samples cannot explicate three phenomena simultaneously: (1) Given enough…
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information
Guanchun Wang, Xiangrong Zhang, Zelin Peng +3
Weakly supervised object detection (WSOD) is a challenging task, in which image-level labels (e.g., categories of the instances in the whole image) are used to train an object dete…
Transformers Meet Visual Learning Understanding: A Comprehensive Review
Yuting Yang, Licheng Jiao, Xu Liu +4
Dynamic attention mechanism and global modeling ability make Transformer show strong feature learning ability. In recent years, Transformer has become comparable to CNNs methods in…
Adaptively Enhancing Facial Expression Crucial Regions via Local Non-Local Joint Network
Guanghui Shi, Shasha Mao, Shuiping Gou +3
Facial expression recognition (FER) is still one challenging research due to the small inter-class discrepancy in the facial expression data. In view of the significance of facial…
GREN: Graph-Regularized Embedding Network for Weakly-Supervised Disease Localization in X-ray Images
Baolian Qi, Gangming Zhao, Xin Wei +4
Locating diseases in chest X-ray images with few careful annotations saves large human effort. Recent works approached this task with innovative weakly-supervised algorithms such a…
Contralaterally Enhanced Networks for Thoracic Disease Detection
Gangming Zhao, Chaowei Fang, Guanbin Li +2
Identifying and locating diseases in chest X-rays are very challenging, due to the low visual contrast between normal and abnormal regions, and distortions caused by other overlapp…