415 citations · 1.2k across the 53 of their papers we have counts for
13 papers · 1 filter
Clue Me In: Semi-Supervised FGVC with Out-of-Distribution Data
Ruoyi Du, Dongliang Chang, Zhanyu Ma +2
Despite great strides made on fine-grained visual classification (FGVC), current methods are still heavily reliant on fully-supervised paradigms where ample expert labels are calle…
Making a Bird AI Expert Work for You and Me
Dongliang Chang, Kaiyue Pang, Ruoyi Du +3
As powerful as fine-grained visual classification (FGVC) is, responding your query with a bird name of "Whip-poor-will" or "Mallard" probably does not make much sense. This however…
Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification
Chenyu Guo, Jiyang Xie, Kongming Liang +2
Fine-grained visual classification (FGVC) aims to classify sub-classes of objects in the same super-class (e.g., species of birds, models of cars). For the FGVC tasks, the essentia…
CMF: Cascaded Multi-model Fusion for Referring Image Segmentation
Jianhua Yang, Yan Huang, Zhanyu Ma +1
In this work, we address the task of referring image segmentation (RIS), which aims at predicting a segmentation mask for the object described by a natural language expression. Mos…
Channel DropBlock: An Improved Regularization Method for Fine-Grained Visual Classification
Yifeng Ding, Shuwei Dong, Yujun Tong +3
Classifying the sub-categories of an object from the same super-category (e.g., bird) in a fine-grained visual classification (FGVC) task highly relies on mining multiple discrimin…
Deep Metric Learning for Few-Shot Image Classification: A Review of Recent Developments
Xiaoxu Li, Xiaochen Yang, Zhanyu Ma +1
Few-shot image classification is a challenging problem that aims to achieve the human level of recognition based only on a small number of training images. One main solution to few…
DF^2AM: Dual-level Feature Fusion and Affinity Modeling for RGB-Infrared Cross-modality Person Re-identification
Junhui Yin, Zhanyu Ma, Jiyang Xie +3
RGB-infrared person re-identification is a challenging task due to the intra-class variations and cross-modality discrepancy. Existing works mainly focus on learning modality-share…
Unsupervised Person Re-identification via Simultaneous Clustering and Consistency Learning
Junhui Yin, Jiayan Qiu, Siqing Zhang +3
Unsupervised person re-identification (re-ID) has become an important topic due to its potential to resolve the scalability problem of supervised re-ID models. However, existing me…
Duplex Contextual Relation Network for Polyp Segmentation
Zijin Yin, Kongming Liang, Zhanyu Ma +1
Polyp segmentation is of great importance in the early diagnosis and treatment of colorectal cancer. Since polyps vary in their shape, size, color, and texture, accurate polyp segm…
Fine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained Features
Dongliang Chang, Yixiao Zheng, Zhanyu Ma +2
Fine-grained visual classification is a challenging task that recognizes the sub-classes belonging to the same meta-class. Large inter-class similarity and intra-class variance is…
Grad-CAM guided channel-spatial attention module for fine-grained visual classification
Shuai Xu, Dongliang Chang, Jiyang Xie +1
Fine-grained visual classification (FGVC) is becoming an important research field, due to its wide applications and the rapid development of computer vision technologies. The curre…
TLRM: Task-level Relation Module for GNN-based Few-Shot Learning
Yurong Guo, Zhanyu Ma, Xiaoxu Li +1
Recently, graph neural networks (GNNs) have shown powerful ability to handle few-shot classification problem, which aims at classifying unseen samples when trained with limited lab…
Progressive Co-Attention Network for Fine-grained Visual Classification
Tian Zhang, Dongliang Chang, Zhanyu Ma +1
Fine-grained visual classification aims to recognize images belonging to multiple sub-categories within a same category. It is a challenging task due to the inherently subtle varia…