activity
20182026
most citedAB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metrics

45 citations · 136 across the 20 of their papers we have counts for

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12 papers · 1 filter

cs.CV2022★ 2 cited

Semi-supervised 3D Object Detection via Temporal Graph Neural Networks

Jianren Wang, Haiming Gang, Siddharth Ancha +2

3D object detection plays an important role in autonomous driving and other robotics applications. However, these detectors usually require training on large amounts of annotated d…

cs.CV2021

Wanderlust: Online Continual Object Detection in the Real World

Jianren Wang, Xin Wang, Yue Shang-Guan +1

Online continual learning from data streams in dynamic environments is a critical direction in the computer vision field. However, realistic benchmarks and fundamental studies in t…

cs.CV2020★ 2 cited

PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection

Xia Chen, Jianren Wang, David Held +1

Visual data in autonomous driving perception, such as camera image and LiDAR point cloud, can be interpreted as a mixture of two aspects: semantic feature and geometric structure.…

cs.CV2020

Uncertainty-aware Self-supervised 3D Data Association

Jianren Wang, Siddharth Ancha, Yi-Ting Chen +1

3D object trackers usually require training on large amounts of annotated data that is expensive and time-consuming to collect. Instead, we propose leveraging vast unlabeled datase…

cs.CV2020★ 45 cited

AB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metrics

Xinshuo Weng, Jianren Wang, David Held +1

3D multi-object tracking (MOT) is essential to applications such as autonomous driving. Recent work focuses on developing accurate systems giving less attention to computational co…

cs.CV2020★ 10 cited

PanoNet: Real-time Panoptic Segmentation through Position-Sensitive Feature Embedding

Xia Chen, Jianren Wang, Martial Hebert

We propose a simple, fast, and flexible framework to generate simultaneously semantic and instance masks for panoptic segmentation. Our method, called PanoNet, incorporates a clean…

cs.CV2020

Motion Prediction in Visual Object Tracking

Jianren Wang, Yihui He

Visual object tracking (VOT) is an essential component for many applications, such as autonomous driving or assistive robotics. However, recent works tend to develop accurate syste…

cs.CV2020★ 6 cited

Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting

Xinshuo Weng, Jianren Wang, Sergey Levine +2

Many autonomous systems forecast aspects of the future in order to aid decision-making. For example, self-driving vehicles and robotic manipulation systems often forecast future ob…

cs.CV2020★ 1 cited

AlignNet: A Unifying Approach to Audio-Visual Alignment

Jianren Wang, Zhaoyuan Fang, Hang Zhao

We present AlignNet, a model that synchronizes videos with reference audios under non-uniform and irregular misalignments. AlignNet learns the end-to-end dense correspondence betwe…

cs.CV2019★ 2 cited

Deep Mixture Density Network for Probabilistic Object Detection

Yihui He, Jianren Wang

Mistakes/uncertainties in object detection could lead to catastrophes when deploying robots in the real world. In this paper, we measure the uncertainties of object localization to…

cs.CV2019★ 10 cited

Prediction-Tracking-Segmentation

Jianren Wang, Yihui He, Xiaobo Wang +2

We introduce a prediction driven method for visual tracking and segmentation in videos. Instead of solely relying on matching with appearance cues for tracking, we build a predicti…

cs.CV2018★ 41 cited

Bounding Box Regression with Uncertainty for Accurate Object Detection

Yihui He, Chenchen Zhu, Jianren Wang +2

Large-scale object detection datasets (e.g., MS-COCO) try to define the ground truth bounding boxes as clear as possible. However, we observe that ambiguities are still introduced…