49 citations · 60 across the 12 of their papers we have counts for
13 papers
Think-Capture: Active 3D Geometry Acquisition for Spatial Reasoning in Vision-Language Models
Junjie Wang, Zhihao Yuan, Yunhan Tang +7
Vision-Language Models (VLMs) excel at 2D recognition but often fail to maintain consistent 3D relations across sparse viewpoints, leading to spatial hallucinations under occlusion…
Reasoning to Regulate: Chain-of-Thought for Traffic Rule Understanding
Yueru Luo, Xu Yan, Changqing Zhou +5
Understanding and complying with traffic regulations is a safety-critical requirement for autonomous driving, yet remains challenging due to the diversity and context dependence of…
DLWM: Dual Latent World Models enable Holistic Gaussian-centric Pre-training in Autonomous Driving
Yiyao Zhu, Ying Xue, Haiming Zhang +8
Vision-based autonomous driving has gained much attention due to its low costs and excellent performance. Compared with dense BEV (Bird's Eye View) or sparse query models, Gaussian…
Reliev3R: Relieving Feed-forward Reconstruction from Multi-View Geometric Annotations
Youyu Chen, Junjun Jiang, Yueru Luo +4
With recent advances, Feed-forward Reconstruction Models (FFRMs) have demonstrated great potential in reconstruction quality and adaptiveness to multiple downstream tasks. However,…
D-World: An Efficient World Model through Decoupled Dynamic Flow
Haiming Zhang, Xu Yan, Ying Xue +4
This technical report summarizes the second-place solution for the Predictive World Model Challenge held at the CVPR-2024 Workshop on Foundation Models for Autonomous Systems. We i…
RadOcc: Learning Cross-Modality Occupancy Knowledge through Rendering Assisted Distillation
Haiming Zhang, Xu Yan, Dongfeng Bai +5
3D occupancy prediction is an emerging task that aims to estimate the occupancy states and semantics of 3D scenes using multi-view images. However, image-based scene perception enc…
Geometry-Aware Network for Domain Adaptive Semantic Segmentation
Yinghong Liao, Wending Zhou, Xu Yan +3
Measuring and alleviating the discrepancies between the synthetic (source) and real scene (target) data is the core issue for domain adaptive semantic segmentation. Though recent w…
M-3DLaneNet: Exploring Multi-Modal 3D Lane Detection
Yueru Luo, Xu Yan, Chaoda Zheng +5
Estimating accurate lane lines in 3D space remains challenging due to their sparse and slim nature. Previous works mainly focused on using images for 3D lane detection, leading to…
Toward Explainable and Fine-Grained 3D Grounding through Referring Textual Phrases
Zhihao Yuan, Xu Yan, Zhuo Li +4
Recent progress in 3D scene understanding has explored visual grounding (3DVG) to localize a target object through a language description. However, existing methods only consider t…
X-Trans2Cap: Cross-Modal Knowledge Transfer using Transformer for 3D Dense Captioning
Zhihao Yuan, Xu Yan, Yinghong Liao +4
3D dense captioning aims to describe individual objects by natural language in 3D scenes, where 3D scenes are usually represented as RGB-D scans or point clouds. However, only expl…
Comprehensive Visual Question Answering on Point Clouds through Compositional Scene Manipulation
Xu Yan, Zhihao Yuan, Yuhao Du +4
Visual Question Answering on 3D Point Cloud (VQA-3D) is an emerging yet challenging field that aims at answering various types of textual questions given an entire point cloud scen…
Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds
Chaoda Zheng, Xu Yan, Jiantao Gao +4
Current 3D single object tracking approaches track the target based on a feature comparison between the target template and the search area. However, due to the common occlusion in…
PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling
Xu Yan, Chaoda Zheng, Zhen Li +2
Raw point clouds data inevitably contains outliers or noise through acquisition from 3D sensors or reconstruction algorithms. In this paper, we present a novel end-to-end network f…