415 citations · 1.2k across the 53 of their papers we have counts for
54 papers
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification
Jijie Wu, Dongliang Chang, Aneeshan Sain +5
The main challenge for fine-grained few-shot image classification is to learn feature representations with higher inter-class and lower intra-class variations, with a mere few labe…
Learning Invariant Visual Representations for Compositional Zero-Shot Learning
Tian Zhang, Kongming Liang, Ruoyi Du +3
Compositional Zero-Shot Learning (CZSL) aims to recognize novel compositions using knowledge learned from seen attribute-object compositions in the training set. Previous works mai…
Multi-View Active Fine-Grained Recognition
Ruoyi Du, Wenqing Yu, Heqing Wang +4
As fine-grained visual classification (FGVC) being developed for decades, great works related have exposed a key direction -- finding discriminative local regions and revealing sub…
Caption Feature Space Regularization for Audio Captioning
Yiming Zhang, Hong Yu, Ruoyi Du +2
Audio captioning aims at describing the content of audio clips with human language. Due to the ambiguity of audio, different people may perceive the same audio differently, resulti…
Domain Generalization via Frequency-domain-based Feature Disentanglement and Interaction
Jingye Wang, Ruoyi Du, Dongliang Chang +2
Adaptation to out-of-distribution data is a meta-challenge for all statistical learning algorithms that strongly rely on the i.i.d. assumption. It leads to unavoidable labor costs…
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…
Knowledge Transfer Based Fine-grained Visual Classification
Siqing Zhang, Ruoyi Du, Dongliang Chang +2
Fine-grained visual classification (FGVC) aims to distinguish the sub-classes of the same category and its essential solution is to mine the subtle and discriminative regions. Conv…
Dilated-Scale-Aware Attention ConvNet For Multi-Class Object Counting
Wei Xu, Dingkang Liang, Yixiao Zheng +1
Object counting aims to estimate the number of objects in images. The leading counting approaches focus on the single category counting task and achieve impressive performance. Not…
BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification
Xiaoxu Li, Jijie Wu, Zhuo Sun +3
Few-shot learning for fine-grained image classification has gained recent attention in computer vision. Among the approaches for few-shot learning, due to the simplicity and effect…
Your "Flamingo" is My "Bird": Fine-Grained, or Not
Dongliang Chang, Kaiyue Pang, Yixiao Zheng +3
Whether what you see in Figure 1 is a "flamingo" or a "bird", is the question we ask in this paper. While fine-grained visual classification (FGVC) strives to arrive at the former,…
Actor and Action Modular Network for Text-based Video Segmentation
Jianhua Yang, Yan Huang, Kai Niu +3
Text-based video segmentation aims to segment an actor in video sequences by specifying the actor and its performing action with a textual query. Previous methods fail to explicitl…
CC-Loss: Channel Correlation Loss For Image Classification
Zeyu Song, Dongliang Chang, Zhanyu Ma +2
The loss function is a key component in deep learning models. A commonly used loss function for classification is the cross entropy loss, which is a simple yet effective applicatio…