509 citations · 686 across the 14 of their papers we have counts for
18 papers
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection
Yichao Shen, Zigang Geng, Yuhui Yuan +6
We introduce a highly performant 3D object detector for point clouds using the DETR framework. The prior attempts all end up with suboptimal results because they fail to learn accu…
DETR Doesn't Need Multi-Scale or Locality Design
Yutong Lin, Yuhui Yuan, Zheng Zhang +3
This paper presents an improved DETR detector that maintains a "plain" nature: using a single-scale feature map and global cross-attention calculations without specific locality co…
FS-Depth: Focal-and-Scale Depth Estimation from a Single Image in Unseen Indoor Scene
Chengrui Wei, Meng Yang, Lei He +1
It has long been an ill-posed problem to predict absolute depth maps from single images in real (unseen) indoor scenes. We observe that it is essentially due to not only the scale-…
MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection
Zewei Lin, Yanqing Shen, Sanping Zhou +2
In this paper, we propose a novel and effective Multi-Level Fusion network, named as MLF-DET, for high-performance cross-modal 3D object DETection, which integrates both the featur…
How Do In-Context Examples Affect Compositional Generalization?
Shengnan An, Zeqi Lin, Qiang Fu +4
Compositional generalization--understanding unseen combinations of seen primitives--is an essential reasoning capability in human intelligence. The AI community mainly studies this…
Vector-based Representation is the Key: A Study on Disentanglement and Compositional Generalization
Tao Yang, Yuwang Wang, Cuiling Lan +2
Recognizing elementary underlying concepts from observations (disentanglement) and generating novel combinations of these concepts (compositional generalization) are fundamental ab…