19 citations · 24 across the 19 of their papers we have counts for
19 papers
HyperDCM: Dynamic Cluster Memory Replay in Hyperbolic Space for Continual Robotic Navigation Across Scenes
Zhengfei Lu, Jian Yang, Muyu Wang +7
Continual learning in visual navigation remains challenging due to catastrophic forgetting and the difficulties associated with adapting to diverse and evolving environments. To ad…
Curvature-Aware Captioning:Leveraging Geodesic Attention for 3D Scene Understanding
Ziyao He, Yingjie Liu, ZhangYangRui +3
Accurate 3D scene description is fundamental to robotic navigation and augmented reality, yet current dense captioning methods face significant limitations in processing sparse poi…
OMGSR: You Only Need One Mid-timestep Guidance for Real-World Image Super-Resolution
Zhiqiang Wu, Zhaomang Sun, Tong Zhou +7
Denoising Diffusion Probabilistic Models (DDPMs) show promising potential in one-step Real-World Image Super-Resolution (Real-ISR). Current one-step Real-ISR methods typically inje…
NeuroLoc: Encoding Navigation Cells for 6-DOF Camera Localization
Xun Li, Jian Yang, Fenli Jia +10
Recently, camera localization has been widely adopted in autonomous robotic navigation due to its efficiency and convenience. However, autonomous navigation in unknown environments…
Dual-BEV Nav: Dual-layer BEV-based Heuristic Path Planning for Robotic Navigation in Unstructured Outdoor Environments
Jianfeng Zhang, Hanlin Dong, Jian Yang +6
Path planning with strong environmental adaptability plays a crucial role in robotic navigation in unstructured outdoor environments, especially in the case of low-quality location…
Hyperbolic Contrastive Learning for Hierarchical 3D Point Cloud Embedding
Yingjie Liu, Pengyu Zhang, Ziyao He +3
Hyperbolic spaces allow for more efficient modeling of complex, hierarchical structures, which is particularly beneficial in tasks involving multi-modal data. Although hyperbolic g…
PDDFormer: Pairwise Distance Distribution Graph Transformer for Crystal Material Property Prediction
Xiangxiang Shen, Zheng Wan, Lingfeng Wen +7
Crystal structures can be simplified as a periodic point set that repeats across three-dimensional space along an underlying lattice. Traditionally, crystal representation methods…
Relaxed Rotational Equivariance via -Biases in Vision
Zhiqiang Wu, Yingjie Liu, Licheng Sun +7
Group Equivariant Convolution (GConv) can capture rotational equivariance from original data. It assumes uniform and strict rotational equivariance across all features as the trans…
R2Det: Exploring Relaxed Rotation Equivariance in 2D object detection
Zhiqiang Wu, Yingjie Liu, Hanlin Dong +5
Group Equivariant Convolution (GConv) empowers models to explore underlying symmetry in data, improving performance. However, real-world scenarios often deviate from ideal symmetri…
Continual Learning via Manifold Expansion Replay
Zihao Xu, Xuan Tang, Yufei Shi +4
In continual learning, the learner learns multiple tasks in sequence, with data being acquired only once for each task. Catastrophic forgetting is a major challenge to continual le…
Hyperbolic Graph Diffusion Model
Lingfeng Wen, Xuan Tang, Mingjie Ouyang +5
Diffusion generative models (DMs) have achieved promising results in image and graph generation. However, real-world graphs, such as social networks, molecular graphs, and traffic…
Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations
Jianzhang Zheng, Hao Shen, Jian Yang +5
Autoencoders have achieved great success in various computer vision applications. The autoencoder learns appropriate low dimensional image representations through the self-supervis…
Multi-scale Geometry-aware Transformer for 3D Point Cloud Classification
Xian Wei, Muyu Wang, Shing-Ho Jonathan Lin +4
Self-attention modules have demonstrated remarkable capabilities in capturing long-range relationships and improving the performance of point cloud tasks. However, point cloud obje…
Group Equivariant BEV for 3D Object Detection
Hongwei Liu, Jian Yang, Jianfeng Zhang +5
Recently, 3D object detection has attracted significant attention and achieved continuous improvement in real road scenarios. The environmental information is collected from a sing…
Learning from Attacks: Attacking Variational Autoencoder for Improving Image Classification
Jianzhang Zheng, Fan Yang, Hao Shen +4
Adversarial attacks are often considered as threats to the robustness of Deep Neural Networks (DNNs). Various defending techniques have been developed to mitigate the potential neg…
Learning Robust and Lightweight Model through Separable Structured Transformations
Xian Wei, Yanhui Huang, Yangyu Xu +5
With the proliferation of mobile devices and the Internet of Things, deep learning models are increasingly deployed on devices with limited computing resources and memory, and are…
ViR:the Vision Reservoir
Xian Wei, Bin Wang, Mingsong Chen +7
The most recent year has witnessed the success of applying the Vision Transformer (ViT) for image classification. However, there are still evidences indicating that ViT often suffe…
Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections
Xian Wei, Hao Shen, Yuanxiang Li +4
There are some inadequacies in the language description of this paper that require further improvement. This paper is based on a revision of a conference paper. It is now necessary…
1D-Convolutional Capsule Network for Hyperspectral Image Classification
Haitao Zhang, Lingguo Meng, Xian Wei +5
Recently, convolutional neural networks (CNNs) have achieved excellent performances in many computer vision tasks. Specifically, for hyperspectral images (HSIs) classification, CNN…