18 citations · 57 across the 22 of their papers we have counts for
23 papers
ViCo3D: Empowering LiDAR-based Collaborative 3D Object Detection with Vision Foundation Models
Haojie Ren, Songrui Luo, Lingfeng Wang +6
LiDAR-based collaborative 3D perception in Vehicle-to-Everything (V2X) systems typically relies on fusing bird's-eye-view (BEV) features across agents. However, current BEV represe…
Environment-Aware Adaptive Pruning with Interleaved Inference Orchestration for Vision-Language-Action Models
Yuting Huang, Leilei Ding, Zhipeng Tang +7
While Vision-Language-Action (VLA) models hold promise in embodied intelligence, their large parameter counts lead to substantial inference latency that hinders real-time manipulat…
SpatialSplat: Efficient Semantic 3D from Sparse Unposed Images
Yu Sheng, Jiajun Deng, Xinran Zhang +4
A major breakthrough in 3D reconstruction is the feedforward paradigm to generate pixel-wise 3D points or Gaussian primitives from sparse, unposed images. To further incorporate se…
CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous Driving
Junrui Zhang, Chenjie Wang, Jie Peng +4
Imitation learning based planning tasks on the nuPlan dataset have gained great interest due to their potential to generate human-like driving behaviors. However, open-loop trainin…
MSGField: A Unified Scene Representation Integrating Motion, Semantics, and Geometry for Robotic Manipulation
Yu Sheng, Runfeng Lin, Lidian Wang +5
Combining accurate geometry with rich semantics has been proven to be highly effective for language-guided robotic manipulation. Existing methods for dynamic scenes either fail to…
MHRC: Closed-loop Decentralized Multi-Heterogeneous Robot Collaboration with Large Language Models
Wenhao Yu, Jie Peng, Yueliang Ying +3
The integration of large language models (LLMs) with robotics has significantly advanced robots' abilities in perception, cognition, and task planning. The use of natural language…
MM-Gaussian: 3D Gaussian-based Multi-modal Fusion for Localization and Reconstruction in Unbounded Scenes
Chenyang Wu, Yifan Duan, Xinran Zhang +3
Localization and mapping are critical tasks for various applications such as autonomous vehicles and robotics. The challenges posed by outdoor environments present particular compl…
CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks
Beibei Wang, Zijian Yu, Lu Zhang +8
Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems research and development. However, it…
HVDistill: Transferring Knowledge from Images to Point Clouds via Unsupervised Hybrid-View Distillation
Sha Zhang, Jiajun Deng, Lei Bai +3
We present a hybrid-view-based knowledge distillation framework, termed HVDistill, to guide the feature learning of a point cloud neural network with a pre-trained image network in…
EdgeCalib: Multi-Frame Weighted Edge Features for Automatic Targetless LiDAR-Camera Calibration
Xingchen Li, Yifan Duan, Beibei Wang +5
In multimodal perception systems, achieving precise extrinsic calibration between LiDAR and camera is of critical importance. Previous calibration methods often required specific t…
OCC-VO: Dense Mapping via 3D Occupancy-Based Visual Odometry for Autonomous Driving
Heng Li, Yifan Duan, Xinran Zhang +3
Visual Odometry (VO) plays a pivotal role in autonomous systems, with a principal challenge being the lack of depth information in camera images. This paper introduces OCC-VO, a no…
Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection
Yingjie Wang, Jiajun Deng, Yao Li +6
LiDAR and Radar are two complementary sensing approaches in that LiDAR specializes in capturing an object's 3D shape while Radar provides longer detection ranges as well as velocit…
USTC FLICAR: A Sensors Fusion Dataset of LiDAR-Inertial-Camera for Heavy-duty Autonomous Aerial Work Robots
Ziming Wang, Yujiang Liu, Yifan Duan +5
In this paper, we present the USTC FLICAR Dataset, which is dedicated to the development of simultaneous localization and mapping and precise 3D reconstruction of the workspace for…
Deep Reinforcement Learning for Localizability-Enhanced Navigation in Dynamic Human Environments
Yuan Chen, Quecheng Qiu, Xiangyu Liu +5
Reliable localization is crucial for autonomous robots to navigate efficiently and safely. Some navigation methods can plan paths with high localizability (which describes the capa…
OA-DET3D: Embedding Object Awareness as a General Plug-in for Multi-Camera 3D Object Detection
Xiaomeng Chu, Jiajun Deng, Jianmin Ji +3
The recent advance in multi-camera 3D object detection is featured by bird's-eye view (BEV) representation or object queries. However, the ill-posed transformation from image-plane…
TLP: A Deep Learning-based Cost Model for Tensor Program Tuning
Yi Zhai, Yu Zhang, Shuo Liu +4
Tensor program tuning is a non-convex objective optimization problem, to which search-based approaches have proven to be effective. At the core of the search-based approaches lies…
MAROAM: Map-based Radar SLAM through Two-step Feature Selection
Dequan Wang, Yifan Duan, Xiaoran Fan +3
In this letter, we propose MAROAM, a millimeter wave radar-based SLAM framework, which employs a two-step feature selection process to build the global consistent map. Specifically…
TransVG++: End-to-End Visual Grounding with Language Conditioned Vision Transformer
Jiajun Deng, Zhengyuan Yang, Daqing Liu +5
In this work, we explore neat yet effective Transformer-based frameworks for visual grounding. The previous methods generally address the core problem of visual grounding, i.e., mu…
Observing Interventions: A logic for thinking about experiments
Fausto Barbero, Katrin Schulz, Fernando R. Velázquez-Quesada +1
This paper makes a first step towards a logic of learning from experiments. For this, we investigate formal frameworks for modeling the interaction of causal and (qualitative) epis…
DRQN-based 3D Obstacle Avoidance with a Limited Field of View
Yu'an Chen, Guangda Chen, Lifan Pan +4
In this paper, we propose a map-based end-to-end DRL approach for three-dimensional (3D) obstacle avoidance in a partially observed environment, which is applied to achieve autonom…
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting
Xiaomeng Chu, Jiajun Deng, Yao Li +4
As cameras are increasingly deployed in new application domains such as autonomous driving, performing 3D object detection on monocular images becomes an important task for visual…
Multi-Modal 3D Object Detection in Autonomous Driving: a Survey
Yingjie Wang, Qiuyu Mao, Hanqi Zhu +5
In this survey, we first introduce the background of popular sensors used for self-driving, their data properties, and the corresponding object detection algorithms. Next, we discu…
Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
Jiajun Deng, Shaoshuai Shi, Peiwei Li +3
Recent advances on 3D object detection heavily rely on how the 3D data are represented, \emph{i.e.}, voxel-based or point-based representation. Many existing high performance 3D de…