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Learning Adaptive Semantic Gaussian Allocation for 3D Occupancy
Kanglin Ning, Yiran Zhao, Wenrui Li +4
Semantic 3D Gaussians provide a compact representation for 3D semantic occupancy prediction by rendering semantic primitives into a voxel volume under voxel-wise supervision. Recen…
T3HG-Editor: Text-driven 3D Human Garment Editing with Body Priors Embedded in SMPL-X
Shaoru Sun, Xingtao Wang, Zihan Ma +4
While 3D Gaussian Editing (3DGE) has seen substantial progress, text-driven 3D human garment editing remains largely underexplored. Existing 3DGE works typically follow a paradigm…
Towards Accurate Single Panoramic 3D Detection: A Semantic Gaussian Centric Approach
Kanglin Ning, Yiran Zhao, Wenrui Li +3
Three-dimensional object detection in panoramic imagery is crucial for comprehensive scene understanding, yet accurately mapping 2D features to 3D remains a significant challenge.…
PairDropGS: Paired Dropout-Induced Consistency Regularization for Sparse-View Gaussian Splatting
Hantang Li, Qiang Zhu, Xiandong Meng +3
Dropout-based sparse-view 3D Gaussian Splatting (3DGS) methods alleviate overfitting by randomly suppressing Gaussian primitives during training. Existing methods mainly focus on d…
Hyperbolic Distillation: Geometry-Guided Cross-Modal Transfer for Robust 3D Object Detection
Kanglin Ning, Wenrui Li, Houde Quan +3
Cross-modal knowledge distillation has emerged as an effective strategy for integrating point cloud and image features in 3D perception tasks. However, the modality heterogeneity,…
Bridging the Visual-to-Physical Gap: Physically Aligned Representations for Fall Risk Analysis
Xianqi Zhang
Vision-based fall analysis has advanced rapidly, but a key bottleneck remains: visually similarmotions can correspond to very different physical outcomes because small differences…
MRT: Learning Compact Representations with Mixed RWKV-Transformer for Extreme Image Compression
Han Liu, Hengyu Man, Xingtao Wang +2
Recent advances in extreme image compression have revealed that mapping pixel data into highly compact latent representations can significantly improve coding efficiency. However,…
Bidirectional Feature-aligned Motion Transformation for Efficient Dynamic Point Cloud Compression
Xuan Deng, Xingtao Wang, Xiandong Meng +4
Efficient dynamic point cloud compression (DPCC) critically depends on accurate motion estimation and compensation. However, the inherently irregular structure and substantial loca…
PAGCNet: A Pose-Aware and Geometry Constrained Framework for Panoramic Depth Estimation
Kanglin Ning, Ruzhao Chen, Penghong Wang +3
Explicitly modeling room background depth as a geometric constraint has proven effective for panoramic depth estimation. However, reconstructing this background depth for regular e…
PVINet: Point-Voxel Interlaced Network for Point Cloud Compression
Xuan Deng, Xingtao Wang, Xiandong Meng +2
In point cloud compression, the quality of a reconstructed point cloud relies on both the global structure and the local context, with existing methods usually processing global an…
Region-Level Context-Aware Multimodal Understanding
Hongliang Wei, Xianqi Zhang, Xingtao Wang +2
Despite significant progress, existing research on Multimodal Large Language Models (MLLMs) mainly focuses on general visual understanding, overlooking the ability to integrate tex…
T-GVC: Trajectory-Guided Generative Video Coding at Ultra-Low Bitrates
Zhitao Wang, Hengyu Man, Wenrui Li +3
Recent advances in video generation techniques have given rise to an emerging paradigm of generative video coding for Ultra-Low Bitrate (ULB) scenarios by leveraging powerful gener…
Multi-Timescale Motion-Decoupled Spiking Transformer for Audio-Visual Zero-Shot Learning
Wenrui Li, Penghong Wang, Xingtao Wang +3
Audio-visual zero-shot learning (ZSL) has been extensively researched for its capability to classify video data from unseen classes during training. Nevertheless, current methodolo…
RouteWinFormer: A Route-Window Transformer for Middle-range Attention in Image Restoration
Qifan Li, Tianyi Liang, Xingtao Wang +1
Transformer models have recently garnered significant attention in image restoration due to their ability to capture long-range pixel dependencies. However, long-range attention of…
Hyperbolic-constraint Point Cloud Reconstruction from Single RGB-D Images
Wenrui Li, Zhe Yang, Wei Han +3
Reconstructing desired objects and scenes has long been a primary goal in 3D computer vision. Single-view point cloud reconstruction has become a popular technique due to its low c…
Digging into Intrinsic Contextual Information for High-fidelity 3D Point Cloud Completion
Jisheng Chu, Wenrui Li, Xingtao Wang +3
The common occurrence of occlusion-induced incompleteness in point clouds has made point cloud completion (PCC) a highly-concerned task in the field of geometric processing. Existi…
Riemann-based Multi-scale Attention Reasoning Network for Text-3D Retrieval
Wenrui Li, Wei Han, Yandu Chen +4
Due to the challenges in acquiring paired Text-3D data and the inherent irregularity of 3D data structures, combined representation learning of 3D point clouds and text remains une…
SceneDreamer360: Text-Driven 3D-Consistent Scene Generation with Panoramic Gaussian Splatting
Wenrui Li, Fucheng Cai, Yapeng Mi +4
Text-driven 3D scene generation has seen significant advancements recently. However, most existing methods generate single-view images using generative models and then stitch them…