19 citations · 24 across the 19 of their papers we have counts for
12 papers · 1 filter
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…
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…
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…
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 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…