33 citations · 39 across the 9 of their papers we have counts for
9 papers
LaplacianFormer:Rethinking Linear Attention with Laplacian Kernel
Zhe Feng, Sen Lian, Changwei Wang +5
The quadratic complexity of softmax attention presents a major obstacle for scaling Transformers to high-resolution vision tasks. Existing linear attention variants often replace t…
HMR-1: Hierarchical Massage Robot with Vision-Language-Model for Embodied Healthcare
Rongtao Xu, Mingming Yu, Xiaofeng Han +7
The rapid advancement of Embodied Intelligence has opened transformative opportunities in healthcare, particularly in physical therapy and rehabilitation. However, critical challen…
Explicit Temporal-Semantic Modeling for Dense Video Captioning via Context-Aware Cross-Modal Interaction
Mingda Jia, Weiliang Meng, Zenghuang Fu +7
Dense video captioning jointly localizes and captions salient events in untrimmed videos. Recent methods primarily focus on leveraging additional prior knowledge and advanced multi…
DMTrack: Deformable State-Space Modeling for UAV Multi-Object Tracking with Kalman Fusion and Uncertainty-Aware Association
Zenghuang Fu, Xiaofeng Han, Mingda Jia +6
Multi-object tracking (MOT) from unmanned aerial vehicles (UAVs) presents unique challenges due to unpredictable object motion, frequent occlusions, and limited appearance cues inh…
Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision
Xiaofeng Han, Shunpeng Chen, Zenghuang Fu +9
Robot vision has greatly benefited from advancements in multimodal fusion techniques and vision-language models (VLMs). We adopt a task-oriented perspective to systematically revie…
SkinFormer: Learning Statistical Texture Representation with Transformer for Skin Lesion Segmentation
Rongtao Xu, Changwei Wang, Jiguang Zhang +3
Accurate skin lesion segmentation from dermoscopic images is of great importance for skin cancer diagnosis. However, automatic segmentation of melanoma remains a challenging task b…
Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic Segmentation
Rongtao Xu, Changwei Wang, Jiaxi Sun +3
Efficiently training accurate deep models for weakly supervised semantic segmentation (WSSS) with image-level labels is challenging and important. Recently, end-to-end WSSS methods…
MTLDesc: Looking Wider to Describe Better
Changwei Wang, Rongtao Xu, Yuyang Zhang +4
Limited by the locality of convolutional neural networks, most existing local features description methods only learn local descriptors with local information and lack awareness of…
Accurate Lung Nodules Segmentation with Detailed Representation Transfer and Soft Mask Supervision
Changwei Wang, Rongtao Xu, Shibiao Xu +3
Accurate lung lesion segmentation from Computed Tomography (CT) images is crucial to the analysis and diagnosis of lung diseases such as COVID-19 and lung cancer. However, the smal…