84 citations · 208 across the 30 of their papers we have counts for
31 papers
Socialality Anchors: Towards Group-bounded Trajectory Prediction
Ziqian Zou, Conghao Wong, Qinmu Peng +1
Trajectory prediction is a key component for understanding human behavior patterns in dynamic scenes. Researchers have devoted substantial efforts to modeling social interactions,…
Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation
Wanli Ma, Jiangwen Lu, Qinmu Peng +1
Training-free open-vocabulary semantic segmentation (OVSS) partitions an image into semantically distinct regions based on arbitrary text descriptions, without learning any additio…
Prototype-Guided Curriculum Learning for Zero-Shot Learning
Lei Wang, Shiming Chen, Guo-Sen Xie +4
In Zero-Shot Learning (ZSL), embedding-based methods enable knowledge transfer from seen to unseen classes by learning a visual-semantic mapping from seen-class images to class-lev…
Who Walks With You Matters: Perceiving Social Interactions with Groups for Pedestrian Trajectory Prediction
Ziqian Zou, Conghao Wong, Beihao Xia +2
Understanding and anticipating human movement has become more critical and challenging in diverse applications such as autonomous driving and surveillance. The complex interactions…
Generalized Sparse Additive Model with Unknown Link Function
Peipei Yuan, Xinge You, Hong Chen +2
Generalized additive models (GAM) have been successfully applied to high dimensional data analysis. However, most existing methods cannot simultaneously estimate the link function,…
What Happens Without Background? Constructing Foreground-Only Data for Fine-Grained Tasks
Yuetian Wang, Wenjin Hou, Qinmu Peng +1
Fine-grained recognition, a pivotal task in visual signal processing, aims to distinguish between similar subclasses based on discriminative information present in samples. However…
Towards Unsupervised Graph Completion Learning on Graphs with Features and Structure Missing
Sichao Fu, Qinmu Peng, Yang He +2
In recent years, graph neural networks (GNN) have achieved significant developments in a variety of graph analytical tasks. Nevertheless, GNN's superior performance will suffer fro…
Detail Reinforcement Diffusion Model: Augmentation Fine-Grained Visual Categorization in Few-Shot Conditions
Tianxu Wu, Shuo Ye, Shuhuang Chen +2
The challenge in fine-grained visual categorization lies in how to explore the subtle differences between different subclasses and achieve accurate discrimination. Previous researc…
Another Vertical View: A Hierarchical Network for Heterogeneous Trajectory Prediction via Spectrums
Beihao Xia, Conghao Wong, Duanquan Xu +2
With the fast development of AI-related techniques, the applications of trajectory prediction are no longer limited to easier scenes and trajectories. More and more trajectories wi…
Semantic-visual Guided Transformer for Few-shot Class-incremental Learning
Wenhao Qiu, Sichao Fu, Jingyi Zhang +2
Few-shot class-incremental learning (FSCIL) has recently attracted extensive attention in various areas. Existing FSCIL methods highly depend on the robustness of the feature backb…
Filter Pruning based on Information Capacity and Independence
Xiaolong Tang, Shuo Ye, Yufeng Shi +3
Filter pruning has gained widespread adoption for the purpose of compressing and speeding up convolutional neural networks (CNNs). However, existing approaches are still far from p…
Self-supervised Guided Hypergraph Feature Propagation for Semi-supervised Classification with Missing Node Features
Chengxiang Lei, Sichao Fu, Yuetian Wang +4
Graph neural networks (GNNs) with missing node features have recently received increasing interest. Such missing node features seriously hurt the performance of the existing GNNs.…
Deep Manifold Hashing: A Divide-and-Conquer Approach for Semi-Paired Unsupervised Cross-Modal Retrieval
Yufeng Shi, Xinge You, Jiamiao Xu +3
Hashing that projects data into binary codes has shown extraordinary talents in cross-modal retrieval due to its low storage usage and high query speed. Despite their empirical suc…
Deep Supervised Information Bottleneck Hashing for Cross-modal Retrieval based Computer-aided Diagnosis
Yufeng Shi, Shuhuang Chen, Xinge You +3
Mapping X-ray images, radiology reports, and other medical data as binary codes in the common space, which can assist clinicians to retrieve pathology-related data from heterogeneo…
MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning
Shiming Chen, Ziming Hong, Guo-Sen Xie +5
The key challenge of zero-shot learning (ZSL) is how to infer the latent semantic knowledge between visual and attribute features on seen classes, and thus achieving a desirable kn…
CSCNet: Contextual Semantic Consistency Network for Trajectory Prediction in Crowded Spaces
Beihao Xia, Conghao Wong, Qinmu Peng +2
Trajectory prediction aims to predict the movement trend of the agents like pedestrians, bikers, vehicles. It is helpful to analyze and understand human activities in crowded space…
TransZero: Attribute-guided Transformer for Zero-Shot Learning
Shiming Chen, Ziming Hong, Yang Liu +6
Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic knowledge from seen classes to unseen ones. Semantic knowledge is learned from attribute descripti…
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning
Shiming Chen, Guo-Sen Xie, Yang Liu +5
Zero-shot learning (ZSL) tackles the unseen class recognition problem, transferring semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable knowledge…
View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums
Conghao Wong, Beihao Xia, Ziming Hong +5
Understanding and forecasting future trajectories of agents are critical for behavior analysis, robot navigation, autonomous cars, and other related applications. Previous methods…
FREE: Feature Refinement for Generalized Zero-Shot Learning
Shiming Chen, Wenjie Wang, Beihao Xia +4
Generalized zero-shot learning (GZSL) has achieved significant progress, with many efforts dedicated to overcoming the problems of visual-semantic domain gap and seen-unseen bias.…
MSN: Multi-Style Network for Trajectory Prediction
Conghao Wong, Beihao Xia, Qinmu Peng +2
Trajectory prediction aims to forecast agents' possible future locations considering their observations along with the video context. It is strongly needed by many autonomous platf…
BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction
Beihao Xia, Conghao Wong, Heng Li +3
Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors. However, they hardly impose the dynamic effects on agents' a…
CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network
Shiming Chen, Wenjie Wang, Beihao Xia +3
Generative adversarial networks (GANs) have been a popular deep generative model for real-world applications. Despite many recent efforts on GANs that have been contributed, mode c…
Modal Regression based Structured Low-rank Matrix Recovery for Multi-view Learning
Jiamiao Xu, Fangzhao Wang, Qinmu Peng +4
Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods…