activity
20202026
most citedTransCrowd: weakly-supervised crowd counting with transformers

270 citations · 488 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

When Numbers Speak: Aligning Textual Numerals and Visual Instances in Text-to-Video Diffusion Models

Zhengyang Sun, Yu Chen, Xin Zhou +4

Text-to-video diffusion models have enabled open-ended video synthesis, but often struggle with generating the correct number of objects specified in a prompt. We introduce NUMINA…

cs.CV2021★ 191 cited

PRA-Net: Point Relation-Aware Network for 3D Point Cloud Analysis

Silin Cheng, Xiwu Chen, Xinwei He +2

Learning intra-region contexts and inter-region relations are two effective strategies to strengthen feature representations for point cloud analysis. However, unifying the two str…

cs.CV2021

EPNet++: Cascade Bi-directional Fusion for Multi-Modal 3D Object Detection

Zhe Liu, Tengteng Huang, Bingling Li +3

Recently, fusing the LiDAR point cloud and camera image to improve the performance and robustness of 3D object detection has received more and more attention, as these two modaliti…

cs.CV2021★ 270 cited

TransCrowd: weakly-supervised crowd counting with transformers

Dingkang Liang, Xiwu Chen, Wei Xu +2

The mainstream crowd counting methods usually utilize the convolution neural network (CNN) to regress a density map, requiring point-level annotations. However, annotating each per…

cs.CV2020★ 27 cited

EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection

Tengteng Huang, Zhe Liu, Xiwu Chen +1

In this paper, we aim at addressing two critical issues in the 3D detection task, including the exploitation of multiple sensors~(namely LiDAR point cloud and camera image), as wel…