9 papers
ARDepth: Auto-regressive Monocular Depth Estimation with Progressive Visual Conditioning
Zijie Wang, Wei Zhang, Weiming Zhang +4
Diffusion models have recently become the dominant paradigm for monocular depth estimation (MDE). However, they implicitly assume that depth can be recovered as a globally smooth f…
World Models as Group Actions
Zijie Wang, Wei Zhang, Weiming Zhang +4
Video world models have achieved strong visual realism, but this does not ensure that their dynamics are truly governed by actions. In this work, we argue that action faithfulness…
TsallisPGD: Adaptive Gradient Weighting for Adversarial Attacks on Semantic Segmentation
Alexander Matyasko, Xin Lou, Indriyati Atmosukarto +1
Attacking semantic segmentation models is significantly harder than image classification models because an attacker must flip thousands of pixel predictions simultaneously. Standar…
OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives
Zedong Dan, Zijie Wang, Wei Zhang +6
Offline vectorized maps constitute critical infrastructure for high-precision autonomous driving and mapping services. Existing approaches rely predominantly on single ego-vehicle…
LaneDiffusion: Improving Centerline Graph Learning via Prior Injected BEV Feature Generation
Zijie Wang, Weiming Zhang, Wei Zhang +4
Centerline graphs, crucial for path planning in autonomous driving, are traditionally learned using deterministic methods. However, these methods often lack spatial reasoning and s…
VLDrive: Vision-Augmented Lightweight MLLMs for Efficient Language-grounded Autonomous Driving
Ruifei Zhang, Wei Zhang, Xiao Tan +4
Recent advancements in language-grounded autonomous driving have been significantly promoted by the sophisticated cognition and reasoning capabilities of large language models (LLM…
AdaDrive: Self-Adaptive Slow-Fast System for Language-Grounded Autonomous Driving
Ruifei Zhang, Junlin Xie, Wei Zhang +4
Effectively integrating Large Language Models (LLMs) into autonomous driving requires a balance between leveraging high-level reasoning and maintaining real-time efficiency. Existi…
Gradient-based Sampling for Class Imbalanced Semi-supervised Object Detection
Jiaming Li, Xiangru Lin, Wei Zhang +6
Current semi-supervised object detection (SSOD) algorithms typically assume class balanced datasets (PASCAL VOC etc.) or slightly class imbalanced datasets (MS-COCO, etc). This ass…
Decoupled Pseudo-labeling for Semi-Supervised Monocular 3D Object Detection
Jiacheng Zhang, Jiaming Li, Xiangru Lin +6
We delve into pseudo-labeling for semi-supervised monocular 3D object detection (SSM3OD) and discover two primary issues: a misalignment between the prediction quality of 3D and 2D…