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20142022
most citedT-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos

577 citations · 1.3k across the 24 of their papers we have counts for

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Showing 2019 · cs.CVShow all

5 papers · 2 filters

cs.CV2019★ 30 cited

Learning Depth-Guided Convolutions for Monocular 3D Object Detection

Mingyu Ding, Yuqi Huo, Hongwei Yi +4

3D object detection from a single image without LiDAR is a challenging task due to the lack of accurate depth information. Conventional 2D convolutions are unsuitable for this task…

cs.CV2019★ 185 cited

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

Shaoshuai Shi, Chaoxu Guo, Li Jiang +4

We present a novel and high-performance 3D object detection framework, named PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds. Our proposed method deep…

cs.CV2019★ 1 cited

Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow

Mingyu Ding, Zhe Wang, Bolei Zhou +3

A major challenge for video semantic segmentation is the lack of labeled data. In most benchmark datasets, only one frame of a video clip is annotated, which makes most supervised…

cs.CV2019★ 13 cited

Robust Multi-Modality Multi-Object Tracking

Wenwei Zhang, Hui Zhou, Shuyang Sun +3

Multi-sensor perception is crucial to ensure the reliability and accuracy in autonomous driving system, while multi-object tracking (MOT) improves that by tracing sequential moveme…

cs.CV2019★ 99 cited

From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network

Shaoshuai Shi, Zhe Wang, Jianping Shi +2

3D object detection from LiDAR point cloud is a challenging problem in 3D scene understanding and has many practical applications. In this paper, we extend our preliminary work Poi…