31 citations · 33 across the 15 of their papers we have counts for
15 papers
GaussianDWM++: Language-Grounded 3D Gaussian Driving World Model for Unified Scene Understanding, Editing, and Multi-Modal Generation
Tianchen Deng, Xuefeng Chen, Shuang Wu +5
Driving World Models (DWMs) have recently advanced rapidly with generative models, yet most existing methods mainly focus on conditional scene generation and lack explicit 3D scene…
Multi-Submap Implicit Neural SLAM with Local-to-Global Loop Closure for Large-Scale Scene Reconstruction
Tianchen Deng, Chongdi Wang, Nailin Wang +6
Neural Radiance Fields (NeRF)-based SLAM has demonstrated impressive results in small-scale scene reconstruction, yet scaling these methods to extensive, complex environments remai…
ViT-Up: Faithful Feature Upsampling for Vision Transformers
Krispin Wandel, Jingchuan Wang, Hesheng Wang
Vision Transformers (ViTs) have become a dominant architecture for visual representation learning, providing exceptionally strong and broadly reusable backbone features. However, V…
Mamba-VGGT: Persistent Long-Sequence Video Geometry Grounded Transformer via External Sliding Window Mamba Memory
Tianchen Deng, Zhenxiang Xiong, Nailin Wang +4
Visual Geometry Grounded Transformers (VGGT) have set new benchmarks in high-fidelity 3D scene reconstruction. However, as the sequence length increases, these models suffer from c…
VGGT-Occ: Geometry-Grounded and Density-Aware Gated Fusion for 3D Occupancy Prediction
Xun Chen, Tianchen Deng, Rui Wang +5
3D semantic occupancy prediction requires accurate 2D-to-3D feature lifting, yet current methods restrict camera geometry to initial projections. Subsequent operations like offset…
Appearance Decomposition Gaussian Splatting for Multi-Traversal Reconstruction
Yangyi Xiao, Siting Zhu, Baoquan Yang +3
Multi-traversal scene reconstruction is important for high-fidelity autonomous driving simulation and digital twin construction. This task involves integrating multiple sequences c…
What Is The Best 3D Scene Representation for Robotics? From Geometric to Foundation Models
Tianchen Deng, Yue Pan, Shenghai Yuan +10
In this paper, we provide a comprehensive overview of existing scene representation methods for robotics, covering traditional representations such as point clouds, voxels, signed…
Reloc-VGGT: Visual Re-localization with Geometry Grounded Transformer
Tianchen Deng, Wenhua Wu, Kunzhen Wu +7
Visual localization has traditionally been formulated as a pair-wise pose regression problem. Existing approaches mainly estimate relative poses between two images and employ a lat…
MUT3R: Motion-aware Updating Transformer for Dynamic 3D Reconstruction
Guole Shen, Tianchen Deng, Xingrui Qin +6
Recent stateful recurrent neural networks have achieved remarkable progress on static 3D reconstruction but remain vulnerable to motion-induced artifacts, where non-rigid regions c…
GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation
Tianchen Deng, Xuefeng Chen, Yi Chen +8
Driving World Models (DWMs) have been developing rapidly with the advances of generative models. However, existing DWMs lack 3D scene understanding capabilities and can only genera…
UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer
Tianchen Deng, Xun Chen, Ziming Li +5
Visual Place Recognition (VPR) has been traditionally formulated as a single-image retrieval task. Using multiple views offers clear advantages, yet this setting remains relatively…
MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation
Tianchen Deng, Guole Shen, Xun Chen +9
Neural implicit scene representations have recently shown promising results in dense visual SLAM. However, existing implicit SLAM algorithms are constrained to single-agent scenari…
CAD-SLAM: Consistency-Aware Dynamic SLAM with Dynamic-Static Decoupled Mapping
Wenhua Wu, Chenpeng Su, Siting Zhu +6
Recent advances in neural radiation fields (NeRF) and 3D Gaussian-based SLAM have achieved impressive localization accuracy and high-quality dense mapping in static scenes. However…
VPGS-SLAM: Voxel-based Progressive 3D Gaussian SLAM in Large-Scale Scenes
Tianchen Deng, Wenhua Wu, Junjie He +4
3D Gaussian Splatting has recently shown promising results in dense visual SLAM. However, existing 3DGS-based SLAM methods are all constrained to small-room scenarios and struggle…
NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and Denoising
Tianchen Deng, Yanbo Wang, Hongle Xie +4
In recent years, there have been significant advancements in 3D reconstruction and dense RGB-D SLAM systems. One notable development is the application of Neural Radiance Fields (N…