MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Rohith Pillai – MSR Thesis Talk

Zoom

ZOOM Link: https://cmu.zoom.us/j/95344974779?pwd=aXlmbktDMFZIUjhyeTRuNWxmeXcwdz09 Meeting ID: 953 4497 4779 Passcode: 783497   Title:  3D Face Reconstruction from Monocular Video and its Applications In the Wild   Abstract: 3D face reconstruction is a very popular field of computer vision due to its applications in social media, entertainment and health. However, ever since the introduction of 3D morphable models as [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk – Hans Kumar

Title: Multi-Session Periodic SLAM for Legged Robots   Abstract: Methods for state estimation that rely on visual information are challenging on dynamic robots because of rapid changes in the viewing angle of onboard cameras. In this thesis, we show that by leveraging structure in the way that dynamic robots locomote, we can increase the feasibility [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Eagle Dapeng Zhao

Title: Predicting Human Trajectories by Learning and Matching Patterns Zoom Link: https://cmu.zoom.us/j/93356993095?pwd=Nzd3a09PbG9mVkV5blFVaU5nRk1GQT09 Abstract: As more and more robots are envisioned to cooperate with humans sharing the same space, it is desired for robots to be able to predict others' trajectories to navigate in a safe and self-explanatory way. We propose a Convolutional Neural Network-based approach [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Shengcao Cao

Title: Efficient Model Performance Estimation via Feature Histories Abstract: An important step in the task of neural network design, such as hyper-parameter optimization (HPO) or neural architecture search (NAS), is the evaluation of a candidate model's performance. Given fixed computational resources, one can either invest more time training each model to obtain more accurate estimates [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Steven Lee

Title: Learning to Represent and Accurately Arrange Food Items   Abstract: Arrangements of objects are commonplace in a myriad of everyday scenarios, such as decorations at one’s home, displays at museums, and plates of food at restaurants. An efficient personal robot should be able to learn how to robustly recreate an arrangement using only a few [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Amrita Sawhney

Title: Learning to Perceive and Manipulate Diverse Food Materials Through Interaction Abstract: The home kitchen environment presents many challenges for an autonomous cooking robot, such as the deformability of food items, the wide range of material properties of food, and the complex interaction dynamics involved in food manipulation tasks. Material properties are important when interacting [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Haidar Jamal

Zoom

Title: Localization for Lunar Micro-Rovers   Abstract: This talk presents an avionics and localization system that enables a lunar micro-rover to navigate autonomously. This system is important for the latest class of small, low-powered, and fast robots going to the Moon in search of polar ice. The first component of the system is an Extended [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Akash Sharma

Title: Incorporating Semantic Structure in SLAM Abstract: For robots to understand the environment they interact with, a combination of geometric information and semantic information is imperative. In this talk, I propose a fast and scalable Simultaneous Localization and Mapping (SLAM) system that represents indoor scenes as a graph of semantic objects. Leveraging the observation that [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Yaadhav Raaj MSR Thesis Talk

Title: Exploiting Uncertainty in Triangulation Light Curtains for Object Tracking and Depth Estimation   Abstract: Active sensing through the use of Adaptive Depth Sensors is a nascent field, with potential in areas such as Advanced driver-assistance systems (ADAS). One such class of sensor is the Triangulation Light Curtain, which was developed in the Illumination and Imaging [...]