MSR Speaking Qualifier
Extern
Robotics Institute,
Carnegie Mellon University

Sha (Yisha) Yi – MSR Thesis Talk

NSH 4305

Title: Improving Scalability in Multi-Robot Systems with Abstraction and Specialization   Abstract: Planning and controlling multi-robot systems is challenging due to high dimensionality. When the number of robots increases in the system, the complexity of computation grows exponentially. In this thesis, we examine the scalability problem in planning and control of the multi-robot system. We propose [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk – Andy (Chieh-En) Tsai

NSH 3305

Title: A Generative Approach for Socially Compliant Navigation   Abstract: Robots navigating in human crowds need to optimize their paths not only for the efficiency of their tasks performance but also for the compliance to social norms. One of the key challenges in this context is due to the lack of suitable metrics for evaluating and [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Shubham Agrawal – MSR Thesis Talk

NSH 4305

Title: 3D Face Geometry Capture Using Monocular Video   Abstract: Accurate reconstruction of facial geometry has been one of the oldest tasks in computer vision. Despite being a long-studied problem, many modern methods fail to reconstruct realistic looking faces or rely on highly constrained environments for capture. High fidelity face reconstructions have so far been [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Tejas Khot – MSR Thesis Talk

NSH 4305

Title: Unsupervised Learning for 3D Reconstruction and Blocks World Representation Abstract: Recovering the dense 3D structure of a scene from its images has been a long-standing goal in computer vision. Recent years have seen attempts of encoding richer priors into the geometry-based pipelines with the introduction of learning based methods. We argue that the form of 3D [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Yubo Zhang – MSR Thesis Talk

NSH 4305

Title: A structured model for action detection   Abstract:  A dominant paradigm for learning-based approaches in computer vision is training generic models, such as ResNet for image recognition, or I3D for video understanding, on large datasets and allowing them to discover the optimal representation for the problem at hand. While this is an obviously attractive approach, [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Nilesh Kulkarni – MSR Thesis Talk

NSH 4305

Title: Canonical Surface Mapping via Geometric Cycle Consistency   Abstract: We explore the task of Canonical Surface Mapping (CSM).  Specifically, given an image, we learn to map pixels on the object to their corresponding locations on an abstract 3D model of the category. But how do we learn such a mapping? A supervised approach would [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Yufei (Judy) Ye – MSR Thesis Talk

NSH 3305

Title: Leveraging Structure for Generalization and Prediction in Visual System. Abstract: Our surrounding world is highly structured. Humans have a great capacity of understanding and leveraging those structures to generalize to novel scenarios and to predict the future. The thesis studies how computer vision systems benefit from the similar process -- leveraging inherent structures in [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Dhiraj Gandhi – MSR Thesis Talk

NSH 4305

Title: Self-Supervised Robot Learning   Abstract: Supervised learning has been used in robotics to solve various tasks like navigation, fine manipulation, etc.  While it has shown a promising result, in most cases the supervision comes from the human agent.  However, relying on human is a huge bottleneck to scale up these approaches.  In this thesis, [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk – Chia Dai

NSH 4305

Title: Few-Shot Learning for Semantic Segmentation   Abstract:  Most learning architectures for segmentation task require a significant amount of data and annotations, especially in the task of segmentation, where each pixel is assigned to a class. Few-shot segmentation aims to replace large amount of training data with only a few densely annotated samples. In this talk, [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Subhodeep Mitra – MSR Thesis Talk

NSH 4305

Title: A fast algorithm for consecutive ones with applications in item labeling   Abstract: We develop and analyze a general problem in a crowd-sourced setting: users pick a label from a set of candidates for a set of items; the problem is to determine the most likely label for each item, as well as a ranking [...]