activity
20192026
most citedACNet: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation

25 citations · 48 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

OPTIAGENT: A Physics-Driven Agentic Framework for Automated Optical Design

Yuyu Geng, Lei Sun, Yao Gao +6

Optical design is the process of configuring optical elements to precisely manipulate light for high-fidelity imaging. It is inherently a highly non-convex optimization problem tha…

cs.CV2022★ 5 cited

CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers

Jiaming Zhang, Huayao Liu, Kailun Yang +3

Scene understanding based on image segmentation is a crucial component of autonomous vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting compleme…

cs.CV2021★ 1 cited

Capturing Omni-Range Context for Omnidirectional Segmentation

Kailun Yang, Jiaming Zhang, Simon Reiß +2

Convolutional Networks (ConvNets) excel at semantic segmentation and have become a vital component for perception in autonomous driving. Enabling an all-encompassing view of street…

cs.CV2020★ 9 cited

Real-time Fusion Network for RGB-D Semantic Segmentation Incorporating Unexpected Obstacle Detection for Road-driving Images

Lei Sun, Kailun Yang, Xinxin Hu +2

Semantic segmentation has made striking progress due to the success of deep convolutional neural networks. Considering the demands of autonomous driving, real-time semantic segment…

cs.CV2019★ 8 cited

DS-PASS: Detail-Sensitive Panoramic Annular Semantic Segmentation through SwaftNet for Surrounding Sensing

Kailun Yang, Xinxin Hu, Hao Chen +3

Semantically interpreting the traffic scene is crucial for autonomous transportation and robotics systems. However, state-of-the-art semantic segmentation pipelines are dominantly…

cs.CV2019★ 25 cited

ACNet: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation

Xinxin Hu, Kailun Yang, Lei Fei +1

Compared to RGB semantic segmentation, RGBD semantic segmentation can achieve better performance by taking depth information into consideration. However, it is still problematic fo…