128 citations · 424 across the 59 of their papers we have counts for
5 papers · 1 filter
EfficientNeRF: Efficient Neural Radiance Fields
Tao Hu, Shu Liu, Yilun Chen +2
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes. It takes long per-scene training time and per-image testing…
Unifying Voxel-based Representation with Transformer for 3D Object Detection
Yanwei Li, Yilun Chen, Xiaojuan Qi +3
In this work, we present a unified framework for multi-modality 3D object detection, named UVTR. The proposed method aims to unify multi-modality representations in the voxel space…
Multi-View Transformer for 3D Visual Grounding
Shijia Huang, Yilun Chen, Jiaya Jia +1
The 3D visual grounding task aims to ground a natural language description to the targeted object in a 3D scene, which is usually represented in 3D point clouds. Previous works stu…
DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors
Yilun Chen, Shijia Huang, Shu Liu +2
Camera-based 3D object detectors are welcome due to their wider deployment and lower price than LiDAR sensors. We first revisit the prior stereo detector DSGN for its stereo volume…
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers
Xuyang Bai, Zeyu Hu, Xinge Zhu +4
LiDAR and camera are two important sensors for 3D object detection in autonomous driving. Despite the increasing popularity of sensor fusion in this field, the robustness against i…