33 citations · 45 across the 19 of their papers we have counts for
22 papers
MIVIFI: Bridging Perspective and Fisheye Domains for Training Multi-View Fisheye Image Generation Models
Matthias Neuwirth-Trapp, Begüm Altunbas, Jiayi Wang +4
Achieving 360° coverage is critical for the visual perception systems of autonomous vehicles. Fisheye cameras offer a cost-effective solution by enabling full surround coverage wit…
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…
Labimus: A Simulation and Benchmark for Humanoid Dexterous Manipulation in Chemical Laboratory
Yuhan Wu, Zhao Jin, Tao Li +9
Laboratory automation has made remarkable progress through robotic platforms and AI-driven scientific reasoning. However, many laboratory operations (e.g., solid--solid transfer) r…
SemCityLoc: Aerial 6DoF Localization Using Semantic 3D City Models
Jingfeng Mao, Xuyang Chen, Qilin Zhang +6
Aerial 6DoF localization typically relies on precise GNSS signals or radiometrically rich 3D reconstructions, limiting scalability and on-board deployment. We propose SemCityLoc, a…
ArtiBench and ArtiBrain: Benchmarking Generalizable Vision-Language Articulated Object Manipulation
Yuhan Wu, Tiantian Wei, Shuo Wang +4
Interactive articulated manipulation requires long-horizon, multi-step interactions with appliances while maintaining physical consistency. Existing vision-language and diffusion-b…
Text2Loc++: Generalizing 3D Point Cloud Localization from Natural Language
Yan Xia, Letian Shi, Yilin Di +2
We tackle the problem of localizing 3D point cloud submaps using complex and diverse natural language descriptions, and present Text2Loc++, a novel neural network designed for effe…
True Multimodal In-Context Learning Needs Attention to the Visual Context
Shuo Chen, Jianzhe Liu, Zhen Han +5
Multimodal Large Language Models (MLLMs), built on powerful language backbones, have enabled Multimodal In-Context Learning (MICL)-adapting to new tasks from a few multimodal demon…
RADLER: Radar Object Detection Leveraging Semantic 3D City Models and Self-Supervised Radar-Image Learning
Yuan Luo, Rudolf Hoffmann, Yan Xia +4
Semantic 3D city models are worldwide easy-accessible, providing accurate, object-oriented, and semantic-rich 3D priors. To date, their potential to mitigate the noise impact on ra…
OPAL: Visibility-aware LiDAR-to-OpenStreetMap Place Recognition via Adaptive Radial Fusion
Shuhao Kang, Martin Y. Liao, Yan Xia +3
LiDAR place recognition is a critical capability for autonomous navigation and cross-modal localization in large-scale outdoor environments. Existing approaches predominantly depen…
Reconstructing Humans with a Biomechanically Accurate Skeleton
Yan Xia, Xiaowei Zhou, Etienne Vouga +2
In this paper, we introduce a method for reconstructing 3D humans from a single image using a biomechanically accurate skeleton model. To achieve this, we train a transformer that…
MonoCT: Overcoming Monocular 3D Detection Domain Shift with Consistent Teacher Models
Johannes Meier, Louis Inchingolo, Oussema Dhaouadi +3
We tackle the problem of monocular 3D object detection across different sensors, environments, and camera setups. In this paper, we introduce a novel unsupervised domain adaptation…
FacaDiffy: Inpainting Unseen Facade Parts Using Diffusion Models
Thomas Froech, Olaf Wysocki, Yan Xia +4
High-detail semantic 3D building models are frequently utilized in robotics, geoinformatics, and computer vision. One key aspect of creating such models is employing 2D conflict ma…
ZAHA: Introducing the Level of Facade Generalization and the Large-Scale Point Cloud Facade Semantic Segmentation Benchmark Dataset
Olaf Wysocki, Yue Tan, Thomas Froech +5
Facade semantic segmentation is a long-standing challenge in photogrammetry and computer vision. Although the last decades have witnessed the influx of facade segmentation methods,…
UniLoc: Towards Universal Place Recognition Using Any Single Modality
Yan Xia, Zhendong Li, Yun-Jin Li +4
To date, most place recognition methods focus on single-modality retrieval. While they perform well in specific environments, cross-modal methods offer greater flexibility by allow…
TrafficLoc: Localizing Traffic Surveillance Cameras in 3D Scenes
Yan Xia, Yunxiang Lu, Rui Song +3
We tackle the problem of localizing traffic cameras within a 3D reference map and propose a novel image-to-point cloud registration (I2P) method, TrafficLoc, in a coarse-tofine mat…
TRASE: Tracking-free 4D Segmentation and Editing
Yun-Jin Li, Mariia Gladkova, Yan Xia +1
Understanding dynamic 3D scenes is crucial for extended reality (XR) and autonomous driving. Incorporating semantic information into 3D reconstruction enables holistic scene repres…
World-Grounded Human Motion Recovery via Gravity-View Coordinates
Zehong Shen, Huaijin Pi, Yan Xia +6
We present a novel method for recovering world-grounded human motion from monocular video. The main challenge lies in the ambiguity of defining the world coordinate system, which v…
TARGO: Benchmarking Target-driven Object Grasping under Occlusions
Yan Xia, Ran Ding, Ziyuan Qin +5
Recent advances in predicting 6D grasp poses from a single depth image have led to promising performance in robotic grasping. However, previous grasping models face challenges in c…
Localizing Events in Videos with Multimodal Queries
Gengyuan Zhang, Mang Ling Ada Fok, Jialu Ma +5
Localizing events in videos based on semantic queries is a pivotal task in video understanding, with the growing significance of user-oriented applications like video search. Yet,…
VXP: Voxel-Cross-Pixel Large-scale Image-LiDAR Place Recognition
Yun-Jin Li, Mariia Gladkova, Yan Xia +2
Cross-modal place recognition methods are flexible GPS-alternatives under varying environment conditions and sensor setups. However, this task is non-trivial since extracting consi…
Text2Loc: 3D Point Cloud Localization from Natural Language
Yan Xia, Letian Shi, Zifeng Ding +2
We tackle the problem of 3D point cloud localization based on a few natural linguistic descriptions and introduce a novel neural network, Text2Loc, that fully interprets the semant…
SCP: Scene Completion Pre-training for 3D Object Detection
Yiming Shan, Yan Xia, Yuhong Chen +1
3D object detection using LiDAR point clouds is a fundamental task in the fields of computer vision, robotics, and autonomous driving. However, existing 3D detectors heavily rely o…