activity
20142023
most citedHorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions

185 citations · 396 across the 19 of their papers we have counts for

collaborators

19 papers

cs.CV2023

Dense Hybrid Proposal Modulation for Lane Detection

Yuejian Wu, Linqing Zhao, Jiwen Lu +1

In this paper, we present a dense hybrid proposal modulation (DHPM) method for lane detection. Most existing methods perform sparse supervision on a subset of high-scoring proposal…

cs.CV20231 cited

LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images

Hui Li, Tianyang Xu, Xiao-Jun Wu +2

Deep learning based fusion methods have been achieving promising performance in image fusion tasks. This is attributed to the network architecture that plays a very important role…

cs.CV2023

Learning Accurate Performance Predictors for Ultrafast Automated Model Compression

Ziwei Wang, Jiwen Lu, Han Xiao +2

In this paper, we propose an ultrafast automated model compression framework called SeerNet for flexible network deployment. Conventional non-differen-tiable methods discretely sea…

cs.CV20231 cited

Binarizing Sparse Convolutional Networks for Efficient Point Cloud Analysis

Xiuwei Xu, Ziwei Wang, Jie Zhou +1

In this paper, we propose binary sparse convolutional networks called BSC-Net for efficient point cloud analysis. We empirically observe that sparse convolution operation causes la…

cs.CV20232 cited

Efficient Meshy Neural Fields for Animatable Human Avatars

Xiaoke Huang, Yiji Cheng, Yansong Tang +3

Efficiently digitizing high-fidelity animatable human avatars from videos is a challenging and active research topic. Recent volume rendering-based neural representations open a ne…

cs.CV2022

A Simple Baseline for Multi-Camera 3D Object Detection

Yunpeng Zhang, Wenzhao Zheng, Zheng Zhu +3

3D object detection with surrounding cameras has been a promising direction for autonomous driving. In this paper, we present SimMOD, a Simple baseline for Multi-camera Object Dete…