6 papers
Guided Diffusion-based Generation of Adversarial Objects for Real-World Monocular Depth Estimation Attacks
Yongtao Chen, Yanbo Wang, Wentao Zhao +3
Monocular Depth Estimation (MDE) serves as a core perception module in autonomous driving systems, but it remains highly susceptible to adversarial attacks. Errors in depth estimat…
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…
GRS-SLAM3R: Real-Time Dense SLAM with Gated Recurrent State
Guole Shen, Tianchen Deng, Yanbo Wang +4
DUSt3R-based end-to-end scene reconstruction has recently shown promising results in dense visual SLAM. However, most existing methods only use image pairs to estimate pointmaps, o…
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…
PLGSLAM: Progressive Neural Scene Represenation with Local to Global Bundle Adjustment
Tianchen Deng, Guole Shen, Tong Qin +5
Neural implicit scene representations have recently shown encouraging results in dense visual SLAM. However, existing methods produce low-quality scene reconstruction and low-accur…