5 papers
UniT: Unified Geometry Learning with Group Autoregressive Transformer
Haotian Wang, Yusong Huang, Zhaonian Kuang +4
Recent feed-forward models have significantly advanced geometry perception for inferring dense 3D structure from sensor observations. However, its essential capabilities remain fra…
CoIn3D: Revisiting Configuration-Invariant Multi-Camera 3D Object Detection
Zhaonian Kuang, Rui Ding, Haotian Wang +3
Multi-camera 3D object detection (MC3D) has attracted increasing attention with the growing deployment of multi-sensor physical agents, such as robots and autonomous vehicles. Howe…
RayD3D: Distilling Depth Knowledge Along the Ray for Robust Multi-View 3D Object Detection
Rui Ding, Zhaonian Kuang, Zongwei Zhou +3
Multi-view 3D detection with bird's eye view (BEV) is crucial for autonomous driving and robotics, but its robustness in real-world is limited as it struggles to predict accurate d…
Object-Scene-Camera Decomposition and Recomposition for Data-Efficient Monocular 3D Object Detection
Zhaonian Kuang, Rui Ding, Meng Yang +2
Monocular 3D object detection (M3OD) is intrinsically ill-posed, hence training a high-performance deep learning based M3OD model requires a humongous amount of labeled data with c…
Jigsaw++: Imagining Complete Shape Priors for Object Reassembly
Jiaxin Lu, Gang Hua, Qixing Huang
The automatic assembly problem has attracted increasing interest due to its complex challenges that involve 3D representation. This paper introduces Jigsaw++, a novel generative me…