1 citations · 2 across the 8 of their papers we have counts for
9 papers
UnPose: Uncertainty-Guided Diffusion Priors for Zero-Shot Pose Estimation
Zhaodong Jiang, Ashish Sinha, Tongtong Cao +3
Estimating the 6D pose of novel objects is a fundamental yet challenging problem in robotics, often relying on access to object CAD models. However, acquiring such models can be co…
HIPPo: Harnessing Image-to-3D Priors for Model-free Zero-shot 6D Pose Estimation
Yibo Liu, Zhaodong Jiang, Binbin Xu +7
This work focuses on model-free zero-shot 6D object pose estimation for robotics applications. While existing methods can estimate the precise 6D pose of objects, they heavily rely…
UniGaussian: Driving Scene Reconstruction from Multiple Camera Models via Unified Gaussian Representations
Yuan Ren, Guile Wu, Runhao Li +5
Urban scene reconstruction is crucial for real-world autonomous driving simulators. Although existing methods have achieved photorealistic reconstruction, they mostly focus on pinh…
3DArticCyclists: Generating Synthetic Articulated 8D Pose-Controllable Cyclist Data for Computer Vision Applications
Eduardo R. Corral-Soto, Yang Liu, Tongtong Cao +2
In Autonomous Driving (AD) Perception, cyclists are considered safety-critical scene objects. Commonly used publicly-available AD datasets typically contain large amounts of car an…
AutoSplat: Constrained Gaussian Splatting for Autonomous Driving Scene Reconstruction
Mustafa Khan, Hamidreza Fazlali, Dhruv Sharma +4
Realistic scene reconstruction and view synthesis are essential for advancing autonomous driving systems by simulating safety-critical scenarios. 3D Gaussian Splatting excels in re…
Analysis of a Modular Autonomous Driving Architecture: The Top Submission to CARLA Leaderboard 2.0 Challenge
Weize Zhang, Mohammed Elmahgiubi, Kasra Rezaee +8
In this paper we present the architecture of the Kyber-E2E submission to the map track of CARLA Leaderboard 2.0 Autonomous Driving (AD) challenge 2023, which achieved first place.…
Learning Effective NeRFs and SDFs Representations with 3D Generative Adversarial Networks for 3D Object Generation
Zheyuan Yang, Yibo Liu, Guile Wu +4
We present a solution for 3D object generation of ICCV 2023 OmniObject3D Challenge. In recent years, 3D object generation has made great process and achieved promising results, but…
GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point Clouds
Ziyu Li, Jingming Guo, Tongtong Cao +2
LiDAR-based 3D detection has made great progress in recent years. However, the performance of 3D detectors is considerably limited when deployed in unseen environments, owing to th…
How to Build a Curb Dataset with LiDAR Data for Autonomous Driving
Dongfeng Bai, Tongtong Cao, Jingming Guo +1
Curbs are one of the essential elements of urban and highway traffic environments. Robust curb detection provides road structure information for motion planning in an autonomous dr…