9 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…
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…
KiteRunner: Language-Driven Cooperative Local-Global Navigation Policy with UAV Mapping in Outdoor Environments
Shibo Huang, Chenfan Shi, Jian Yang +8
Autonomous navigation in open-world outdoor environments faces challenges in integrating dynamic conditions, long-distance spatial reasoning, and semantic understanding. Traditiona…
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…
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…