Search Results for author: Xiaoqing Ye

Found 35 papers, 14 papers with code

PointMamba: A Simple State Space Model for Point Cloud Analysis

1 code implementation16 Feb 2024 Dingkang Liang, Xin Zhou, Xinyu Wang, Xingkui Zhu, Wei Xu, Zhikang Zou, Xiaoqing Ye, Xiang Bai

Recently, state space models (SSM), a new family of deep sequence models, have presented great potential for sequence modeling in NLP tasks.

DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

no code implementations11 Oct 2023 Xiaofan Li, Yifu Zhang, Xiaoqing Ye

To alleviate the problem, we propose a spatial-temporal consistent diffusion framework DrivingDiffusion, to generate realistic multi-view videos controlled by 3D layout.

Autonomous Driving Image Generation +1

Forward Flow for Novel View Synthesis of Dynamic Scenes

no code implementations ICCV 2023 Xiang Guo, Jiadai Sun, Yuchao Dai, GuanYing Chen, Xiaoqing Ye, Xiao Tan, Errui Ding, Yumeng Zhang, Jingdong Wang

This paper proposes a neural radiance field (NeRF) approach for novel view synthesis of dynamic scenes using forward warping.

Novel View Synthesis

SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model

1 code implementation4 Jun 2023 Dingyuan Zhang, Dingkang Liang, Hongcheng Yang, Zhikang Zou, Xiaoqing Ye, Zhe Liu, Xiang Bai

In the spirit of unleashing the capability of foundation models on vision tasks, the Segment Anything Model (SAM), a vision foundation model for image segmentation, has been proposed recently and presents strong zero-shot ability on many downstream 2D tasks.

3D Object Detection Image Segmentation +3

Multi-Modal 3D Object Detection by Box Matching

1 code implementation12 May 2023 Zhe Liu, Xiaoqing Ye, Zhikang Zou, Xinwei He, Xiao Tan, Errui Ding, Jingdong Wang, Xiang Bai

Extensive experiments on the nuScenes dataset demonstrate that our method is much more stable in dealing with challenging cases such as asynchronous sensors, misaligned sensor placement, and degenerated camera images than existing fusion methods.

3D Object Detection Autonomous Driving +2

SOOD: Towards Semi-Supervised Oriented Object Detection

1 code implementation CVPR 2023 Wei Hua, Dingkang Liang, Jingyu Li, Xiaolong Liu, Zhikang Zou, Xiaoqing Ye, Xiang Bai

Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years.

Object object-detection +4

ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Box

no code implementations27 Mar 2023 Yifu Zhang, Xinggang Wang, Xiaoqing Ye, Wei zhang, Jincheng Lu, Xiao Tan, Errui Ding, Peize Sun, Jingdong Wang

We propose a hierarchical data association strategy to mine the true objects in low-score detection boxes, which alleviates the problems of object missing and fragmented trajectories.

3D Multi-Object Tracking motion prediction +1

IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformation

1 code implementation ICCV 2023 Jianhui Liu, Yukang Chen, Xiaoqing Ye, Xiaojuan Qi

Category-level 6D pose estimation aims to predict the poses and sizes of unseen objects from a specific category.

6D Pose Estimation

StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection

no code implementations4 Jan 2023 Zhe Liu, Xiaoqing Ye, Xiao Tan, Errui Ding, Xiang Bai

In this paper, we propose a cross-modal distillation method named StereoDistill to narrow the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors from the superior LiDAR model at the response level, which is usually overlooked in 3D object detection distillation.

3D Object Detection object-detection

Command-Driven Articulated Object Understanding and Manipulation

no code implementations CVPR 2023 Ruihang Chu, Zhengzhe Liu, Xiaoqing Ye, Xiao Tan, Xiaojuan Qi, Chi-Wing Fu, Jiaya Jia

The key of Cart is to utilize the prediction of object structures to connect visual observations with user commands for effective manipulations.

motion prediction Object +1

Repainting and Imitating Learning for Lane Detection

no code implementations11 Oct 2022 Yue He, Minyue Jiang, Xiaoqing Ye, Liang Du, Zhikang Zou, Wei zhang, Xiao Tan, Errui Ding

In this paper, we target at finding an enhanced feature space where the lane features are distinctive while maintaining a similar distribution of lanes in the wild.

Lane Detection

Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation

1 code implementation8 Oct 2022 Peizhe Jiang, Wei Yang, Xiaoqing Ye, Xiao Tan, Meng Wu

Monocular depth estimation (MDE) in the self-supervised scenario has emerged as a promising method as it refrains from the requirement of ground truth depth.

Data Augmentation Monocular Depth Estimation

SoccerNet 2022 Challenges Results

7 code implementations5 Oct 2022 Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.

Action Spotting Camera Calibration +3

Spatial Pruned Sparse Convolution for Efficient 3D Object Detection

no code implementations28 Sep 2022 Jianhui Liu, Yukang Chen, Xiaoqing Ye, Zhuotao Tian, Xiao Tan, Xiaojuan Qi

3D scenes are dominated by a large number of background points, which is redundant for the detection task that mainly needs to focus on foreground objects.

3D Object Detection Object +1

Paint and Distill: Boosting 3D Object Detection with Semantic Passing Network

no code implementations12 Jul 2022 Bo Ju, Zhikang Zou, Xiaoqing Ye, Minyue Jiang, Xiao Tan, Errui Ding, Jingdong Wang

In this work, we propose a novel semantic passing framework, named SPNet, to boost the performance of existing lidar-based 3D detection models with the guidance of rich context painting, with no extra computation cost during inference.

3D Object Detection Autonomous Driving +1

GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation

no code implementations16 Apr 2022 Shi Gong, Xiaoqing Ye, Xiao Tan, Jingdong Wang, Errui Ding, Yu Zhou, Xiang Bai

Birds-eye-view (BEV) semantic segmentation is critical for autonomous driving for its powerful spatial representation ability.

Autonomous Driving Image Segmentation +2

Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task

no code implementations25 Mar 2022 Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding

On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.

Autonomous Driving Monocular 3D Object Detection +1

Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task

no code implementations CVPR 2022 Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding

On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.

Autonomous Driving Monocular 3D Object Detection +1

SGM3D: Stereo Guided Monocular 3D Object Detection

1 code implementation3 Dec 2021 Zheyuan Zhou, Liang Du, Xiaoqing Ye, Zhikang Zou, Xiao Tan, Li Zhang, xiangyang xue, Jianfeng Feng

Monocular 3D object detection aims to predict the object location, dimension and orientation in 3D space alongside the object category given only a monocular image.

Autonomous Driving Depth Estimation +4

Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network

no code implementations27 Jul 2021 Zhikang Zou, Xiaoye Qu, Pan Zhou, Shuangjie Xu, Xiaoqing Ye, Wenhao Wu, Jin Ye

In specific, at the coarse-grained stage, we design a dual-discriminator strategy to adapt source domain to be close to the targets from the perspectives of both global and local feature space via adversarial learning.

Crowd Counting Transfer Learning

Revealing the Reciprocal Relations Between Self-Supervised Stereo and Monocular Depth Estimation

no code implementations ICCV 2021 Zhi Chen, Xiaoqing Ye, Wei Yang, Zhenbo Xu, Xiao Tan, Zhikang Zou, Errui Ding, Xinming Zhang, Liusheng Huang

Second, we introduce an occlusion-aware distillation (OA Distillation) module, which leverages the predicted depths from StereoNet in non-occluded regions to train our monocular depth estimation network named SingleNet.

Monocular Depth Estimation Stereo Matching

ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection

1 code implementation1 Mar 2020 Zhenbo Xu, Wei zhang, Xiaoqing Ye, Xiao Tan, Wei Yang, Shilei Wen, Errui Ding, Ajin Meng, Liusheng Huang

The pipeline of ZoomNet begins with an ordinary 2D object detection model which is used to obtain pairs of left-right bounding boxes.

3D Object Detection Autonomous Driving +2

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