56 citations · 262 across the 66 of their papers we have counts for
15 papers · 1 filter
Bootstrap Masked Visual Modeling via Hard Patches Mining
Haochen Wang, Junsong Fan, Yuxi Wang +4
Masked visual modeling has attracted much attention due to its promising potential in learning generalizable representations. Typical approaches urge models to predict specific con…
Open-sourced Data Ecosystem in Autonomous Driving: the Present and Future
Hongyang Li, Yang Li, Huijie Wang +16
With the continuous maturation and application of autonomous driving technology, a systematic examination of open-source autonomous driving datasets becomes instrumental in fosteri…
Merlin:Empowering Multimodal LLMs with Foresight Minds
En Yu, Liang Zhao, Yana Wei +8
Humans possess the remarkable ability to foresee the future to a certain extent based on present observations, a skill we term as foresight minds. However, this capability remains…
Panacea: Panoramic and Controllable Video Generation for Autonomous Driving
Yuqing Wen, Yucheng Zhao, Yingfei Liu +7
The field of autonomous driving increasingly demands high-quality annotated training data. In this paper, we propose Panacea, an innovative approach to generate panoramic and contr…
ADriver-I: A General World Model for Autonomous Driving
Fan Jia, Weixin Mao, Yingfei Liu +5
Typically, autonomous driving adopts a modular design, which divides the full stack into perception, prediction, planning and control parts. Though interpretable, such modular desi…
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…
TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning
Dongming Wu, Jiahao Chang, Fan Jia +3
Topology reasoning aims to comprehensively understand road scenes and present drivable routes in autonomous driving. It requires detecting road centerlines (lane) and traffic eleme…
Language Prompt for Autonomous Driving
Dongming Wu, Wencheng Han, Yingfei Liu +4
A new trend in the computer vision community is to capture objects of interest following flexible human command represented by a natural language prompt. However, the progress of u…
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…
OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation
Dongming Wu, Tiancai Wang, Yuang Zhang +2
Referring video object segmentation (RVOS) aims at segmenting an object in a video following human instruction. Current state-of-the-art methods fall into an offline pattern, in wh…
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…
MOTRv3: Release-Fetch Supervision for End-to-End Multi-Object Tracking
En Yu, Tiancai Wang, Zhuoling Li +3
Although end-to-end multi-object trackers like MOTR enjoy the merits of simplicity, they suffer from the conflict between detection and association seriously, resulting in unsatisf…
Referring Multi-Object Tracking
Dongming Wu, Wencheng Han, Tiancai Wang +3
Existing referring understanding tasks tend to involve the detection of a single text-referred object. In this paper, we propose a new and general referring understanding task, ter…
Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection
Shihao Wang, Yingfei Liu, Tiancai Wang +2
In this paper, we propose a long-sequence modeling framework, named StreamPETR, for multi-view 3D object detection. Built upon the sparse query design in the PETR series, we system…
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…