331 citations · 1.5k across the 73 of their papers we have counts for
34 papers · 1 filter
A Vision-Centric Approach for Static Map Element Annotation
Jiaxin Zhang, Shiyuan Chen, Haoran Yin +5
The recent development of online static map element (a.k.a. HD Map) construction algorithms has raised a vast demand for data with ground truth annotations. However, available publ…
MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction
Bencheng Liao, Shaoyu Chen, Yunchi Zhang +5
High-definition (HD) map provides abundant and precise static environmental information of the driving scene, serving as a fundamental and indispensable component for planning in a…
ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration
Jiaqi Ma, Tianheng Cheng, Guoli Wang +3
Image restoration aims to reconstruct degraded images, e.g., denoising or deblurring. Existing works focus on designing task-specific methods and there are inadequate attempts at u…
RoMe: Towards Large Scale Road Surface Reconstruction via Mesh Representation
Ruohong Mei, Wei Sui, Jiaxin Zhang +4
In autonomous driving applications, accurate and efficient road surface reconstruction is paramount. This paper introduces RoMe, a novel framework designed for the robust reconstru…
TinyDet: Accurate Small Object Detection in Lightweight Generic Detectors
Shaoyu Chen, Tianheng Cheng, Jiemin Fang +4
Small object detection requires the detection head to scan a large number of positions on image feature maps, which is extremely hard for computation- and energy-efficient lightwei…
VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene
Shaoyu Chen, Yunchi Zhang, Bencheng Liao +7
High-definition (HD) map serves as the essential infrastructure of autonomous driving. In this work, we build up a systematic vectorized map annotation framework (termed VMA) for e…
DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation
Deyu An, Qiang Zhang, Jianshu Chao +4
Unmanned aerial vehicles (UAVs) are frequently used for inspecting power lines and capturing high-resolution aerial images. However, detecting power lines in aerial images is diffi…
OpenInst: A Simple Query-Based Method for Open-World Instance Segmentation
Cheng Wang, Guoli Wang, Qian Zhang +3
Open-world instance segmentation has recently gained significant popularitydue to its importance in many real-world applications, such as autonomous driving, robot perception, and…
Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction
Bencheng Liao, Shaoyu Chen, Bo Jiang +5
Online lane graph construction is a promising but challenging task in autonomous driving. Previous methods usually model the lane graph at the pixel or piece level, and recover the…
Towards Accurate Ground Plane Normal Estimation from Ego-Motion
Jiaxin Zhang, Wei Sui, Qian Zhang +2
In this paper, we introduce a novel approach for ground plane normal estimation of wheeled vehicles. In practice, the ground plane is dynamically changed due to braking and unstabl…
Perceive, Interact, Predict: Learning Dynamic and Static Clues for End-to-End Motion Prediction
Bo Jiang, Shaoyu Chen, Xinggang Wang +7
Motion prediction is highly relevant to the perception of dynamic objects and static map elements in the scenarios of autonomous driving. In this work, we propose PIP, the first en…
BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance Segmentation
Tianheng Cheng, Xinggang Wang, Shaoyu Chen +2
Labeling objects with pixel-wise segmentation requires a huge amount of human labor compared to bounding boxes. Most existing methods for weakly supervised instance segmentation fo…
ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative Transformer
Jiaqi Ma, Shengyuan Yan, Lefei Zhang +2
In order to get raw images of high quality for downstream Image Signal Process (ISP), in this paper we present an Efficient Locally Multiplicative Transformer called ELMformer for…
MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction
Bencheng Liao, Shaoyu Chen, Xinggang Wang +4
High-definition (HD) map provides abundant and precise environmental information of the driving scene, serving as a fundamental and indispensable component for planning in autonomo…
Vision-based Uneven BEV Representation Learning with Polar Rasterization and Surface Estimation
Zhi Liu, Shaoyu Chen, Xiaojie Guo +6
In this work, we propose PolarBEV for vision-based uneven BEV representation learning. To adapt to the foreshortening effect of camera imaging, we rasterize the BEV space both angu…
Polar Parametrization for Vision-based Surround-View 3D Detection
Shaoyu Chen, Xinggang Wang, Tianheng Cheng +3
3D detection based on surround-view camera system is a critical technique in autopilot. In this work, we present Polar Parametrization for 3D detection, which reformulates position…
Featurized Query R-CNN
Wenqiang Zhang, Tianheng Cheng, Xinggang Wang +3
The query mechanism introduced in the DETR method is changing the paradigm of object detection and recently there are many query-based methods have obtained strong object detection…
Differentiable Point-Based Radiance Fields for Efficient View Synthesis
Qiang Zhang, Seung-Hwan Baek, Szymon Rusinkiewicz +1
We propose a differentiable rendering algorithm for efficient novel view synthesis. By departing from volume-based representations in favor of a learned point representation, we im…
AziNorm: Exploiting the Radial Symmetry of Point Cloud for Azimuth-Normalized 3D Perception
Shaoyu Chen, Xinggang Wang, Tianheng Cheng +4
Studying the inherent symmetry of data is of great importance in machine learning. Point cloud, the most important data format for 3D environmental perception, is naturally endowed…
Sparse Instance Activation for Real-Time Instance Segmentation
Tianheng Cheng, Xinggang Wang, Shaoyu Chen +5
In this paper, we propose a conceptually novel, efficient, and fully convolutional framework for real-time instance segmentation. Previously, most instance segmentation methods hea…
Learning Quality-aware Representation for Multi-person Pose Regression
Yabo Xiao, Dongdong Yu, Xiaojuan Wang +3
Off-the-shelf single-stage multi-person pose regression methods generally leverage the instance score (i.e., confidence of the instance localization) to indicate the pose quality f…
AdaptivePose: Human Parts as Adaptive Points
Yabo Xiao, Xiaojuan Wang, Dongdong Yu +3
Multi-person pose estimation methods generally follow top-down and bottom-up paradigms, both of which can be considered as two-stage approaches thus leading to the high computation…
FRNET: Flattened Residual Network for Infant MRI Skull Stripping
Qian Zhang, Li Wang, Xiaopeng Zong +3
Skull stripping for brain MR images is a basic segmentation task. Although many methods have been proposed, most of them focused mainly on the adult MR images. Skull stripping for…
High Fidelity Face Manipulation with Extreme Poses and Expressions
Chaoyou Fu, Yibo Hu, Xiang Wu +3
Face manipulation has shown remarkable advances with the flourish of Generative Adversarial Networks. However, due to the difficulties of controlling structures and textures, it is…