45 citations · 136 across the 20 of their papers we have counts for
20 papers
BRIDGE: An Open-Source Humanoid Platform via Morphology-Control Co-Design for Physical AI
Jianren Wang, Letian Qian, Zikai Wang +4
Developing humanoid robots capable of leveraging human behavioral data is essential for general-purpose embodiment, yet conventional development remains bottlenecked by a decoupled…
One-shot Video Imitation via Parameterized Symbolic Abstraction Graphs
Jianren Wang, Kangni Liu, Dingkun Guo +2
Learning to manipulate dynamic and deformable objects from a single demonstration video holds great promise in terms of scalability. Previous approaches have predominantly focused…
Robot Parkour Learning
Ziwen Zhuang, Zipeng Fu, Jianren Wang +4
Parkour is a grand challenge for legged locomotion that requires robots to overcome various obstacles rapidly in complex environments. Existing methods can generate either diverse…
Manipulate by Seeing: Creating Manipulation Controllers from Pre-Trained Representations
Jianren Wang, Sudeep Dasari, Mohan Kumar Srirama +2
The field of visual representation learning has seen explosive growth in the past years, but its benefits in robotics have been surprisingly limited so far. Prior work uses generic…
Curiosity Driven Self-supervised Tactile Exploration of Unknown Objects
Yujie Lu, Jianren Wang, Vikash Kumar
Intricate behaviors an organism can exhibit is predicated on its ability to sense and effectively interpret complexities of its surroundings. Relevant information is often distribu…
RB2: Robotic Manipulation Benchmarking with a Twist
Sudeep Dasari, Jianren Wang, Joyce Hong +12
Benchmarks offer a scientific way to compare algorithms using objective performance metrics. Good benchmarks have two features: (a) they should be widely useful for many research g…
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…
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…
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.…
CLOUD: Contrastive Learning of Unsupervised Dynamics
Jianren Wang, Yujie Lu, Hang Zhao
Developing agents that can perform complex control tasks from high dimensional observations such as pixels is challenging due to difficulties in learning dynamics efficiently. In t…
SEMI: Self-supervised Exploration via Multisensory Incongruity
Jianren Wang, Ziwen Zhuang, Hang Zhao
Efficient exploration is a long-standing problem in reinforcement learning since extrinsic rewards are usually sparse or missing. A popular solution to this issue is to feed an age…
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…
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…
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…
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…
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…
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…
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…
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…
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…