45 citations · 201 across the 27 of their papers we have counts for
27 papers
UniDet: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection
Yubin Wang, Zhikang Zou, Xiaoqing Ye +3
We present UniDet, a brand new framework for unified and universal multi-dataset training on 3D detection, enabling robust performance across diverse domains and generalization…
Explore the LiDAR-Camera Dynamic Adjustment Fusion for 3D Object Detection
Yiran Yang, Xu Gao, Tong Wang +5
Camera and LiDAR serve as informative sensors for accurate and robust autonomous driving systems. However, these sensors often exhibit heterogeneous natures, resulting in distribut…
Forward Flow for Novel View Synthesis of Dynamic Scenes
Xiang Guo, Jiadai Sun, Yuchao Dai +6
This paper proposes a neural radiance field (NeRF) approach for novel view synthesis of dynamic scenes using forward warping. Existing methods often adopt a static NeRF to represen…
Diffusion-based 3D Object Detection with Random Boxes
Xin Zhou, Jinghua Hou, Tingting Yao +6
3D object detection is an essential task for achieving autonomous driving. Existing anchor-based detection methods rely on empirical heuristics setting of anchors, which makes the…
SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model
Dingyuan Zhang, Dingkang Liang, Hongcheng Yang +4
With the development of large language models, many remarkable linguistic systems like ChatGPT have thrived and achieved astonishing success on many tasks, showing the incredible p…
Multi-Modal 3D Object Detection by Box Matching
Zhe Liu, Xiaoqing Ye, Zhikang Zou +5
Multi-modal 3D object detection has received growing attention as the information from different sensors like LiDAR and cameras are complementary. Most fusion methods for 3D detect…
Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes
Jiang-Tian Zhai, Ze Feng, Jinhao Du +6
Modern autonomous driving systems are typically divided into three main tasks: perception, prediction, and planning. The planning task involves predicting the trajectory of the ego…
SOOD: Towards Semi-Supervised Oriented Object Detection
Wei Hua, Dingkang Liang, Jingyu Li +4
Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years. However, existing SSOD approache…
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model
Dingkang Liang, Jiahao Xie, Zhikang Zou +3
Supervised crowd counting relies heavily on costly manual labeling, which is difficult and expensive, especially in dense scenes. To alleviate the problem, we propose a novel unsup…
ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Box
Yifu Zhang, Xinggang Wang, Xiaoqing Ye +6
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects across video frames. Detection boxes serve as the basis of both 2D and 3D MOT. The inevitabl…
CAPE: Camera View Position Embedding for Multi-View 3D Object Detection
Kaixin Xiong, Shi Gong, Xiaoqing Ye +5
In this paper, we address the problem of detecting 3D objects from multi-view images. Current query-based methods rely on global 3D position embeddings (PE) to learn the geometric…
IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformation
Jianhui Liu, Yukang Chen, Xiaoqing Ye +1
Category-level 6D pose estimation aims to predict the poses and sizes of unseen objects from a specific category. Thanks to prior deformation, which explicitly adapts a category-sp…
StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection
Zhe Liu, Xiaoqing Ye, Xiao Tan +2
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…
Repainting and Imitating Learning for Lane Detection
Yue He, Minyue Jiang, Xiaoqing Ye +5
Current lane detection methods are struggling with the invisibility lane issue caused by heavy shadows, severe road mark degradation, and serious vehicle occlusion. As a result, di…
SoccerNet 2022 Challenges Results
Silvio Giancola, Anthony Cioppa, Adrien Deliège +91
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation
Peizhe Jiang, Wei Yang, Xiaoqing Ye +2
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. Despite continuous eff…
Spatial Pruned Sparse Convolution for Efficient 3D Object Detection
Jianhui Liu, Yukang Chen, Xiaoqing Ye +3
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. In this paper, we analyz…
AGO-Net: Association-Guided 3D Point Cloud Object Detection Network
Liang Du, Xiaoqing Ye, Xiao Tan +5
The human brain can effortlessly recognize and localize objects, whereas current 3D object detection methods based on LiDAR point clouds still report inferior performance for detec…
Paint and Distill: Boosting 3D Object Detection with Semantic Passing Network
Bo Ju, Zhikang Zou, Xiaoqing Ye +4
3D object detection task from lidar or camera sensors is essential for autonomous driving. Pioneer attempts at multi-modality fusion complement the sparse lidar point clouds with r…
Neural Deformable Voxel Grid for Fast Optimization of Dynamic View Synthesis
Xiang Guo, Guanying Chen, Yuchao Dai +4
Recently, Neural Radiance Fields (NeRF) is revolutionizing the task of novel view synthesis (NVS) for its superior performance. In this paper, we propose to synthesize dynamic scen…
GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation
Shi Gong, Xiaoqing Ye, Xiao Tan +4
Birds-eye-view (BEV) semantic segmentation is critical for autonomous driving for its powerful spatial representation ability. It is challenging to estimate the BEV semantic maps f…
Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task
Xiaoqing Ye, Mao Shu, Hanyu Li +5
Concurrent perception datasets for autonomous driving are mainly limited to frontal view with sensors mounted on the vehicle. None of them is designed for the overlooked roadside p…
The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection
Zhikang Zou, Xiaoqing Ye, Liang Du +6
Low-cost monocular 3D object detection plays a fundamental role in autonomous driving, whereas its accuracy is still far from satisfactory. In this paper, we dig into the 3D object…
SGM3D: Stereo Guided Monocular 3D Object Detection
Zheyuan Zhou, Liang Du, Xiaoqing Ye +5
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. It poses a grea…