Student Talks
Carnegie Mellon University
Tanya Marwah – MSR Thesis Talk
Title: Generating 3D Human Animations from Single Monocular Images Abstract: Endowing AI systems with the ability to formulate a three-dimensional understanding of human appearance from a single RGB image is an important component technology for applications such as person re-identification, biometrics, virtual reality and augmented reality. However, jointly inferring the texture map and 3D [...]
Pragna Mannam – MSR Thesis Talk
Title: Model-free Sensorless Manipulation Abstract: This thesis is a study of 2D manipulation without sensing and planning, by exploring the effects of unplanned randomized action sequences on 2D object pose uncertainty. Our approach uses sensorless reorienting of an object to achieve a determined pose, regardless of the initial pose. Without using sensors and models [...]
Carnegie Mellon University
Gines Hidalgo Martinez – MSR Thesis Talk
Title: OpenPose: Whole-Body Pose Estimation Abstract: We present the first single-network approach for 2D whole-body (body, face, hand, and foot) pose estimation, capable of detecting an arbitrary number of people from in-the-wild images. Our method maintains constant real-time performance regardless of the number of people in the image. This network is trained in a [...]
Donglai Xiang – MSR Thesis Talk
Title: Monocular Total Capture: Pose Face, Body, and Hands in the Wild Abstract: We present the first method to capture the 3D total motion of a target person from a monocular view input. Given an image or a monocular video, our method reconstructs the motion from body, face, and fingers represented by a 3D deformable [...]
Carnegie Mellon University
Wentao Yuan – MSR Thesis Talk
Title: 3D Shape Completion and Canonical Pose Estimation with Structured Neural Networks Abstract: 3D point cloud is an efficient and flexible representation of 3D structures and the raw output of many 3D sensors. Recently, neural networks operating on point clouds have shown superior performance on various 3D understanding tasks, thanks to their power to [...]
Carnegie Mellon University
Planning under Uncertainty with Multiple Heuristics
Abstract: Many robotic tasks, such as mobile manipulation, often require interaction with unstructured environments and are subject to imperfect sensing and actuation. This brings substantial uncertainty into the problems. Reasoning under this uncertainty can provide higher level of robustness but is computationally significantly more challenging. More specifically, sequential decision making under motion and sensing uncertainty [...]
Rawal Khirodkar – MSR Thesis Talk
Title: Leveraging Simulation for Computer Vision Abstract: A large amount of labeled data is required to train deep neural networks. The process of data annotation on such a large scale is expensive and time-consuming. A promising alternative in this regard is to use simulation to generate labeled synthetic data. However, a network trained solely [...]
Carnegie Mellon University
Dexterous Manipulation via Simple Robot Hands
Abstract: Most of the industrial robotic applications nowadays can only deal with pick-and-place manipulation, in which fixed graspings are the only interactions between the object and the robot hand. Simple hands, such as pinch grippers and suction cups, suffice to accomplish such tasks. However, there exist many unsolved automation problems where more dexterous manipulations are [...]
Carnegie Mellon University
Maximilian Sieb – MSR Thesis Talk
Title: Visual Imitation Learning for Robot Manipulation Abstract: Imitation learning has been successfully applied to solve a variety of tasks in complex domains where an explicit reward function is not available. However, most imitation learning methods require access to the robot's actions during demonstration. This stands in a stark contrast to how we [...]
Carnegie Mellon University
Enabling Role-Reversible Human-Robot Interaction by Leveraging Standardized Tools for Provider-Receiver Interactions
Abstract: Developing 'social intelligence' for assistive robots to seamlessly interact with humans remains an open research challenge. However, socially assistive robots typically engage in types of interactions that already exist between humans, which makes models of human-human interactions useful to inform the design of robot social behaviors. In particular, in applications such as healthcare, therapy [...]