Search Results for author: Ruigang Yang

Found 68 papers, 32 papers with code

Model2Scene: Learning 3D Scene Representation via Contrastive Language-CAD Models Pre-training

no code implementations29 Sep 2023 Runnan Chen, Xinge Zhu, Nenglun Chen, Dawei Wang, Wei Li, Yuexin Ma, Ruigang Yang, Tongliang Liu, Wenping Wang

In this paper, we propose Model2Scene, a novel paradigm that learns free 3D scene representation from Computer-Aided Design (CAD) models and languages.

3D Semantic Segmentation

LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving

1 code implementation7 Dec 2022 Xiang Li, Junbo Yin, Botian Shi, Yikang Li, Ruigang Yang, Jianbing Shen

In this paper, we present a more artful framework, LiDAR-guided Weakly Supervised Instance Segmentation (LWSIS), which leverages the off-the-shelf 3D data, i. e., Point Cloud, together with the 3D boxes, as natural weak supervisions for training the 2D image instance segmentation models.

Autonomous Driving Instance Segmentation +5

SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud

1 code implementation6 Dec 2022 Yan Wang, Junbo Yin, Wei Li, Pascal Frossard, Ruigang Yang, Jianbing Shen

However, these UDA solutions just yield unsatisfactory 3D detection results when there is a severe domain shift, e. g., from Waymo (64-beam) to nuScenes (32-beam).

3D Object Detection Autonomous Driving +5

Transformation-Equivariant 3D Object Detection for Autonomous Driving

no code implementations22 Nov 2022 Hai Wu, Chenglu Wen, Wei Li, Xin Li, Ruigang Yang, Cheng Wang

However, it is difficult to apply such networks to 3D object detection in autonomous driving due to its large computation cost and slow reasoning speed.

3D Object Detection Autonomous Driving +2

Zero-shot point cloud segmentation by transferring geometric primitives

no code implementations18 Oct 2022 Runnan Chen, Xinge Zhu, Nenglun Chen, Wei Li, Yuexin Ma, Ruigang Yang, Wenping Wang

To this end, we propose a novel framework to learn the geometric primitives shared in seen and unseen categories' objects and employ a fine-grained alignment between language and the learned geometric primitives.

Point Cloud Segmentation Semantic Segmentation

Vision-Centric BEV Perception: A Survey

1 code implementation4 Aug 2022 Yuexin Ma, Tai Wang, Xuyang Bai, Huitong Yang, Yuenan Hou, Yaming Wang, Yu Qiao, Ruigang Yang, Dinesh Manocha, Xinge Zhu

In recent years, vision-centric Bird's Eye View (BEV) perception has garnered significant interest from both industry and academia due to its inherent advantages, such as providing an intuitive representation of the world and being conducive to data fusion.

STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes

1 code implementation CVPR 2022 Peishan Cong, Xinge Zhu, Feng Qiao, Yiming Ren, Xidong Peng, Yuenan Hou, Lan Xu, Ruigang Yang, Dinesh Manocha, Yuexin Ma

In addition, considering the property of sparse global distribution and density-varying local distribution of pedestrians, we further propose a novel method, Density-aware Hierarchical heatmap Aggregation (DHA), to enhance pedestrian perception in crowded scenes.

Pedestrian Detection Sensor Fusion

FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction

1 code implementation1 Nov 2021 Hao Zhu, Haotian Yang, Longwei Guo, Yidi Zhang, Yanru Wang, Mingkai Huang, Menghua Wu, Qiu Shen, Ruigang Yang, Xun Cao

By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input.

3D Face Reconstruction 3D Reconstruction

Referring Self-supervised Learning on 3D Point Cloud

no code implementations29 Sep 2021 Runnan Chen, Xinge Zhu, Nenglun Chen, Dawei Wang, Wei Li, Yuexin Ma, Ruigang Yang, Wenping Wang

In this paper, we study a new problem named Referring Self-supervised Learning (RSL) on 3D scene understanding: Given the 3D synthetic models with labels and the unlabeled 3D real scene scans, our goal is to distinguish the identical semantic objects on an unseen scene according to the referring synthetic 3D models.

Scene Understanding Self-Supervised Learning

Detailed Avatar Recovery from Single Image

no code implementations6 Aug 2021 Hao Zhu, Xinxin Zuo, Haotian Yang, Sen Wang, Xun Cao, Ruigang Yang

In this paper, we propose a novel learning-based framework that combines the robustness of the parametric model with the flexibility of free-form 3D deformation.

Semantic Distribution-aware Contrastive Adaptation for Semantic Segmentation

1 code implementation11 May 2021 Shuang Li, Binhui Xie, Bin Zang, Chi Harold Liu, Xinjing Cheng, Ruigang Yang, Guoren Wang

Specifically, we first design a pixel-wise contrastive loss by considering the correspondences between semantic distributions and pixel-wise representations from both domains.

Self-Supervised Learning Semantic Segmentation

LEAD: LiDAR Extender for Autonomous Driving

no code implementations16 Feb 2021 Jianing Zhang, Wei Li, Honggang Gou, Lu Fang, Ruigang Yang

In this paper, we propose LEAD, i. e., LiDAR Extender for Autonomous Driving, to extend the MEMS LiDAR by coupled image w. r. t both FoV and range.

Autonomous Driving Depth Completion +1

Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data Augmentation

1 code implementation15 Dec 2020 Feixiang Lu, Zongdai Liu, Hui Miao, Peng Wang, Liangjun Zhang, Ruigang Yang, Dinesh Manocha, Bin Zhou

For autonomous driving, the dynamics and states of vehicle parts such as doors, the trunk, and the bonnet can provide meaningful semantic information and interaction states, which are essential to ensuring the safety of the self-driving vehicle.

Autonomous Driving Data Augmentation +3

DVI: Depth Guided Video Inpainting for Autonomous Driving

2 code implementations ECCV 2020 Miao Liao, Feixiang Lu, Dingfu Zhou, Sibo Zhang, Wei Li, Ruigang Yang

To get clear street-view and photo-realistic simulation in autonomous driving, we present an automatic video inpainting algorithm that can remove traffic agents from videos and synthesize missing regions with the guidance of depth/point cloud.

Autonomous Driving Image Inpainting +2

Speech2Video Synthesis with 3D Skeleton Regularization and Expressive Body Poses

1 code implementation17 Jul 2020 Miao Liao, Sibo Zhang, Peng Wang, Hao Zhu, Xinxin Zuo, Ruigang Yang

In this paper, we propose a novel approach to convert given speech audio to a photo-realistic speaking video of a specific person, where the output video has synchronized, realistic, and expressive rich body dynamics.

PerMO: Perceiving More at Once from a Single Image for Autonomous Driving

no code implementations16 Jul 2020 Feixiang Lu, Zongdai Liu, Xibin Song, Dingfu Zhou, Wei Li, Hui Miao, Miao Liao, Liangjun Zhang, Bin Zhou, Ruigang Yang, Dinesh Manocha

We present a novel approach to detect, segment, and reconstruct complete textured 3D models of vehicles from a single image for autonomous driving.

3D Reconstruction Autonomous Driving +3

ODE-CNN: Omnidirectional Depth Extension Networks

no code implementations3 Jul 2020 Xinjing Cheng, Peng Wang, Yanqi Zhou, Chenye Guan, Ruigang Yang

Omnidirectional 360{\deg} camera proliferates rapidly for autonomous robots since it significantly enhances the perception ability by widening the field of view(FoV).

SparseFusion: Dynamic Human Avatar Modeling from Sparse RGBD Images

no code implementations5 Jun 2020 Xinxin Zuo, Sen Wang, Jiangbin Zheng, Weiwei Yu, Minglun Gong, Ruigang Yang, Li Cheng

First, based on a generative human template, for every two frames having sufficient overlap, an initial pairwise alignment is performed; It is followed by a global non-rigid registration procedure, in which partial results from RGBD frames are collected into a unified 3D shape, under the guidance of correspondences from the pairwise alignment; Finally, the texture map of the reconstructed human model is optimized to deliver a clear and spatially consistent texture.

Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution

no code implementations CVPR 2020 Xibin Song, Yuchao Dai, Dingfu Zhou, Liu Liu, Wei Li, Hongdng Li, Ruigang Yang

Second, we propose a new framework for real-world DSR, which consists of four modules : 1) An iterative residual learning module with deep supervision to learn effective high-frequency components of depth maps in a coarse-to-fine manner; 2) A channel attention strategy to enhance channels with abundant high-frequency components; 3) A multi-stage fusion module to effectively re-exploit the results in the coarse-to-fine process; and 4) A depth refinement module to improve the depth map by TGV regularization and input loss.

Benchmarking Depth Map Super-Resolution

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction

1 code implementation CVPR 2020 Haotian Yang, Hao Zhu, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single image input.

A Unified Object Motion and Affinity Model for Online Multi-Object Tracking

1 code implementation CVPR 2020 Junbo Yin, Wenguan Wang, Qinghao Meng, Ruigang Yang, Jianbing Shen

In this paper, we propose a novel MOT framework that unifies object motion and affinity model into a single network, named UMA, in order to learn a compact feature that is discriminative for both object motion and affinity measure.

Metric Learning Multi-Object Tracking +2

Learning 2D-3D Correspondences To Solve The Blind Perspective-n-Point Problem

1 code implementation15 Mar 2020 Liu Liu, Dylan Campbell, Hongdong Li, Dingfu Zhou, Xibin Song, Ruigang Yang

Conventional absolute camera pose via a Perspective-n-Point (PnP) solver often assumes that the correspondences between 2D image pixels and 3D points are given.


Gated Path Selection Network for Semantic Segmentation

no code implementations19 Jan 2020 Qichuan Geng, Hong Zhang, Xiaojuan Qi, Ruigang Yang, Zhong Zhou, Gao Huang

Semantic segmentation is a challenging task that needs to handle large scale variations, deformations and different viewpoints.

Segmentation Semantic Segmentation

Domain-invariant Stereo Matching Networks

1 code implementation ECCV 2020 Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Prisacariu, Benjamin Wah, Philip Torr

State-of-the-art stereo matching networks have difficulties in generalizing to new unseen environments due to significant domain differences, such as color, illumination, contrast, and texture.

Stereo Matching Test

AutoRemover: Automatic Object Removal for Autonomous Driving Videos

1 code implementation28 Nov 2019 Rong Zhang, Wei Li, Peng Wang, Chenye Guan, Jin Fang, Yuhang Song, Jinhui Yu, Baoquan Chen, Weiwei Xu, Ruigang Yang

To deal with shadows, we build up an autonomous driving shadow dataset and design a deep neural network to detect shadows automatically.

Autonomous Driving Video Inpainting

CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion

no code implementations13 Nov 2019 Xinjing Cheng, Peng Wang, Chenye Guan, Ruigang Yang

In this paper, we propose CSPN++, which further improves its effectiveness and efficiency by learning adaptive convolutional kernel sizes and the number of iterations for the propagation, thus the context and computational resources needed at each pixel could be dynamically assigned upon requests.

Depth Completion Stereo-LiDAR Fusion

Learning Resilient Behaviors for Navigation Under Uncertainty

no code implementations22 Oct 2019 Tingxiang Fan, Pinxin Long, Wenxi Liu, Jia Pan, Ruigang Yang, Dinesh Manocha

Deep reinforcement learning has great potential to acquire complex, adaptive behaviors for autonomous agents automatically.

Autonomous Driving

Improved Techniques for Training Adaptive Deep Networks

2 code implementations ICCV 2019 Hao Li, Hong Zhang, Xiaojuan Qi, Ruigang Yang, Gao Huang

Adaptive inference is a promising technique to improve the computational efficiency of deep models at test time.

Knowledge Distillation Test

IoU Loss for 2D/3D Object Detection

1 code implementation11 Aug 2019 Dingfu Zhou, Jin Fang, Xibin Song, Chenye Guan, Junbo Yin, Yuchao Dai, Ruigang Yang

In 2D/3D object detection task, Intersection-over-Union (IoU) has been widely employed as an evaluation metric to evaluate the performance of different detectors in the testing stage.

3D Object Detection object-detection

Adversarial Objects Against LiDAR-Based Autonomous Driving Systems

no code implementations11 Jul 2019 Yulong Cao, Chaowei Xiao, Dawei Yang, Jing Fang, Ruigang Yang, Mingyan Liu, Bo Li

Deep neural networks (DNNs) are found to be vulnerable against adversarial examples, which are carefully crafted inputs with a small magnitude of perturbation aiming to induce arbitrarily incorrect predictions.

Autonomous Driving Test

Detailed Human Shape Estimation from a Single Image by Hierarchical Mesh Deformation

1 code implementation CVPR 2019 Hao Zhu, Xinxin Zuo, Sen Wang, Xun Cao, Ruigang Yang

This paper presents a novel framework to recover detailed human body shapes from a single image.

Salient Object Detection in the Deep Learning Era: An In-Depth Survey

1 code implementation19 Apr 2019 Wenguan Wang, Qiuxia Lai, Huazhu Fu, Jianbing Shen, Haibin Ling, Ruigang Yang

As an essential problem in computer vision, salient object detection (SOD) has attracted an increasing amount of research attention over the years.

object-detection RGB Salient Object Detection +2

GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

3 code implementations CVPR 2019 Feihu Zhang, Victor Prisacariu, Ruigang Yang, Philip H. S. Torr

In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities.

Stereo Depth Estimation Stereo Matching

AADS: Augmented Autonomous Driving Simulation using Data-driven Algorithms

1 code implementation23 Jan 2019 Wei Li, Chengwei Pan, Rong Zhang, Jiaping Ren, Yuexin Ma, Jin Fang, Feilong Yan, Qichuan Geng, Xinyu Huang, Huajun Gong, Weiwei Xu, Guoping Wang, Dinesh Manocha, Ruigang Yang

Our augmented approach combines the flexibility in a virtual environment (e. g., vehicle movements) with the richness of the real world to allow effective simulation of anywhere on earth.

Autonomous Driving

Human Pose Estimation with Spatial Contextual Information

no code implementations7 Jan 2019 Hong Zhang, Hao Ouyang, Shu Liu, Xiaojuan Qi, Xiaoyong Shen, Ruigang Yang, Jiaya Jia

With this principle, we present two conceptually simple and yet computational efficient modules, namely Cascade Prediction Fusion (CPF) and Pose Graph Neural Network (PGNN), to exploit underlying contextual information.

Pose Estimation

ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving

no code implementations CVPR 2019 Xibin Song, Peng Wang, Dingfu Zhou, Rui Zhu, Chenye Guan, Yuchao Dai, Hao Su, Hongdong Li, Ruigang Yang

Specifically, we first segment each car with a pre-trained Mask R-CNN, and then regress towards its 3D pose and shape based on a deformable 3D car model with or without using semantic keypoints.

3D Car Instance Understanding Autonomous Driving

Part-level Car Parsing and Reconstruction from Single Street View

no code implementations27 Nov 2018 Qichuan Geng, Hong Zhang, Xinyu Huang, Sen Wang, Feixiang Lu, Xinjing Cheng, Zhong Zhou, Ruigang Yang

As it is labor-intensive to annotate semantic parts on real street views, we propose a specific approach to implicitly transfer part features from synthesized images to real street views.

Car Pose Estimation Domain Adaptation +1

Augmented LiDAR Simulator for Autonomous Driving

no code implementations17 Nov 2018 Jin Fang, Dingfu Zhou, Feilong Yan, Tongtong Zhao, Feihu Zhang, Yu Ma, Liang Wang, Ruigang Yang

Instead, we can simply deploy a vehicle with a LiDAR scanner to sweep the street of interests to obtain the background point cloud, based on which annotated point cloud can be automatically generated.

Autonomous Driving

TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents

1 code implementation6 Nov 2018 Yuexin Ma, Xinge Zhu, Sibo Zhang, Ruigang Yang, Wenping Wang, Dinesh Manocha

To safely and efficiently navigate in complex urban traffic, autonomous vehicles must make responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles, pedestrians, etc.).

Autonomous Vehicles Navigate +2

Learning Depth with Convolutional Spatial Propagation Network

1 code implementation4 Oct 2018 Xinjing Cheng, Peng Wang, Ruigang Yang

In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for various depth estimation tasks.

Depth Completion Depth Estimation +3

Safe Navigation with Human Instructions in Complex Scenes

no code implementations12 Sep 2018 Zhe Hu, Jia Pan, Tingxiang Fan, Ruigang Yang, Dinesh Manocha

In this paper, we present a robotic navigation algorithm with natural language interfaces, which enables a robot to safely walk through a changing environment with moving persons by following human instructions such as "go to the restaurant and keep away from people".

Collision Avoidance Motion Planning +2

RealPoint3D: Point Cloud Generation from a Single Image with Complex Background

1 code implementation8 Sep 2018 Yan Xia, Yang Zhang, Dingfu Zhou, Xinyu Huang, Cheng Wang, Ruigang Yang

Then, the image together with the retrieved shape model is fed into the proposed network to generate the fine-grained 3D point cloud.

Point Cloud Generation

A Network Structure to Explicitly Reduce Confusion Errors in Semantic Segmentation

no code implementations1 Aug 2018 Qichuan Geng, Xinyu Huang, Zhong Zhou, Ruigang Yang

Confusing classes that are ubiquitous in real world often degrade performance for many vision related applications like object detection, classification, and segmentation.

Image Segmentation object-detection +3

Identity Preserving Face Completion for Large Ocular Region Occlusion

no code implementations23 Jul 2018 Yajie Zhao, Weikai Chen, Jun Xing, Xiaoming Li, Zach Bessinger, Fuchang Liu, WangMeng Zuo, Ruigang Yang

Different from the state-of-the-art face inpainting methods that have no control over the synthesized content and can only handle frontal face pose, our approach can faithfully recover the missing content under various head poses while preserving the identity.

Facial Inpainting

DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map

1 code implementation CVPR 2018 Peng Wang, Ruigang Yang, Binbin Cao, Wei Xu, Yuanqing Lin

The uniqueness of our design is a sensor fusion scheme which integrates camera videos, motion sensors (GPS/IMU), and a 3D semantic map in order to achieve robustness and efficiency of the system.

Autonomous Driving Pose Estimation +2

Learning Warped Guidance for Blind Face Restoration

1 code implementation ECCV 2018 Xiaoming Li, Ming Liu, Yuting Ye, WangMeng Zuo, Liang Lin, Ruigang Yang

For better recovery of fine facial details, we modify the problem setting by taking both the degraded observation and a high-quality guided image of the same identity as input to our guided face restoration network (GFRNet).

Blind Face Restoration

The ApolloScape Open Dataset for Autonomous Driving and its Application

2 code implementations16 Mar 2018 Xinyu Huang, Peng Wang, Xinjing Cheng, Dingfu Zhou, Qichuan Geng, Ruigang Yang

In this paper, we provide a sensor fusion scheme integrating camera videos, consumer-grade motion sensors (GPS/IMU), and a 3D semantic map in order to achieve robust self-localization and semantic segmentation for autonomous driving.

Autonomous Driving Instance Segmentation +3

Mask-off: Synthesizing Face Images in the Presence of Head-mounted Displays

no code implementations26 Oct 2016 Yajie Zhao, Qingguo Xu, Xinyu Huang, Ruigang Yang

The main purpose of this paper is to synthesize realistic face images without occlusions based on the images captured by these cameras.

Colorization Face Alignment +1

Interactive Visual Hull Refinement for Specular and Transparent Object Surface Reconstruction

no code implementations ICCV 2015 Xinxin Zuo, Chao Du, Sen Wang, Jiangbin Zheng, Ruigang Yang

We discovered that these internal contours, which are results of convex parts on an object's surface, can lead to a tighter fit than the original visual hull.

Contour Detection Surface Reconstruction +2

3D Reconstruction in the Presence of Glasses by Acoustic and Stereo Fusion

no code implementations CVPR 2015 Mao Ye, Yu Zhang, Ruigang Yang, Dinesh Manocha

We present a novel sensor fusion algorithm that first segments the depth map into different categories such as opaque/transparent/infinity (e. g., too far to measure) and then updates the depth map based on the segmentation outcome.

3D Reconstruction Sensor Fusion +1

Quality Dynamic Human Body Modeling Using a Single Low-cost Depth Camera

no code implementations CVPR 2014 Qing Zhang, Bo Fu, Mao Ye, Ruigang Yang

In this paper we present a novel autonomous pipeline to build a personalized parametric model (pose-driven avatar) using a single depth sensor.

Data-driven Flower Petal Modeling with Botany Priors

no code implementations CVPR 2014 Chenxi Zhang, Mao Ye, Bo Fu, Ruigang Yang

Each segmented petal is then fitted with a scale-invariant morphable petal shape model, which is constructed from individually scanned exemplar petals.

Real-time Simultaneous Pose and Shape Estimation for Articulated Objects Using a Single Depth Camera

no code implementations CVPR 2014 Mao Ye, Ruigang Yang

In this paper we present a novel real-time algorithm for simultaneous pose and shape estimation for articulated objects, such as human beings and animals.

Pose Estimation

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