activity
20212023
most citedPETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

17 citations · 26 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 1 cited

VLM-Eval: A General Evaluation on Video Large Language Models

Shuailin Li, Yuang Zhang, Yucheng Zhao +4

Despite the rapid development of video Large Language Models (LLMs), a comprehensive evaluation is still absent. In this paper, we introduce a unified evaluation that encompasses m…

cs.CV2023★ 2 cited

Far3D: Expanding the Horizon for Surround-view 3D Object Detection

Xiaohui Jiang, Shuailin Li, Yingfei Liu +5

Recently 3D object detection from surround-view images has made notable advancements with its low deployment cost. However, most works have primarily focused on close perception ra…

cs.CV2023★ 2 cited

The 1st-place Solution for CVPR 2023 OpenLane Topology in Autonomous Driving Challenge

Dongming Wu, Fan Jia, Jiahao Chang +7

We present the 1st-place solution of OpenLane Topology in Autonomous Driving Challenge. Considering that topology reasoning is based on centerline detection and traffic element det…

cs.CV2023★ 3 cited

Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

Junjie Yan, Yingfei Liu, Jianjian Sun +4

In this paper, we propose a robust 3D detector, named Cross Modal Transformer (CMT), for end-to-end 3D multi-modal detection. Without explicit view transformation, CMT takes the im…

cs.CV2022★ 17 cited

PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

Yingfei Liu, Junjie Yan, Fan Jia +5

In this paper, we propose PETRv2, a unified framework for 3D perception from multi-view images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which utilize…

cs.CV2021★ 1 cited

Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation

Shuailin Li, Zhitong Gao, Xuming He

Learning segmentation from noisy labels is an important task for medical image analysis due to the difficulty in acquiring highquality annotations. Most existing methods neglect th…

cs.CV2021

Weakly Supervised Volumetric Segmentation via Self-taught Shape Denoising Model

Qian He, Shuailin Li, Xuming He

Weakly supervised segmentation is an important problem in medical image analysis due to the high cost of pixelwise annotation. Prior methods, while often focusing on weak labels of…