output
20192024
most citedREFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

858 citations

80 papers

cs.LG20247 cited

Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning

Chenjia Bai, Lingxiao Wang, Jianye Hao +4

Offline Reinforcement Learning (RL) has shown promising results in learning a task-specific policy from a fixed dataset. However, successful offline RL often relies heavily on the…

cs.RO202418 cited

S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

Xiao Wang, Ke Tang, Xingyuan Dai +5

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying soc…

cs.CV20241 cited

Calibration & Reconstruction: Deep Integrated Language for Referring Image Segmentation

Yichen Yan, Xingjian He, Sihan Chen +1

Referring image segmentation aims to segment an object referred to by natural language expression from an image. The primary challenge lies in the efficient propagation of fine-gra…

cs.CV20244 cited

Unified Multi-modal Diagnostic Framework with Reconstruction Pre-training and Heterogeneity-combat Tuning

Yupei Zhang, Li Pan, Qiushi Yang +2

Medical multi-modal pre-training has revealed promise in computer-aided diagnosis by leveraging large-scale unlabeled datasets. However, existing methods based on masked autoencode…

cs.CV202430 cited

Hypergraph-based Multi-View Action Recognition using Event Cameras

Yue Gao, Jiaxuan Lu, Siqi Li +2

Action recognition from video data forms a cornerstone with wide-ranging applications. Single-view action recognition faces limitations due to its reliance on a single viewpoint. I…

cs.CV20242 cited

MS-Net: A Multi-Path Sparse Model for Motion Prediction in Multi-Scenes

Xiaqiang Tang, Weigao Sun, Siyuan Hu +2

The multi-modality and stochastic characteristics of human behavior make motion prediction a highly challenging task, which is critical for autonomous driving. While deep learning…