MSR Thesis Talk – Gaurav Parmar
NSH 1109Title: Spatially-Adaptive Multilayer GAN Inversion Abstract: Existing GAN inversion and editing methods are well suited for only a target images that contain aligned objects with a clean background, such as portraits and animal faces, but often struggle for more difficult categories with complex scene layouts and object occlusions, such as cars, animals, and outdoor images. [...]
Robust Reinforcement Learning via Genetic Curriculum
GHC 6501Abstract: Achieving robust performance is crucial when applying deep reinforcement learning (RL) in safety critical systems. Some of the state of the art approaches try to address the problem with adversarial agents, but these agents often require expert supervision to fine tune and prevent the adversary from becoming too challenging to the trainee agent. While [...]
Mouth Haptics in VR using a Headset Ultrasound Phased Array
GHC 7501Abstract: This talk is the same one I will be presenting at the ACM CHI Conference on Human Factors in Computing Systems on May 2nd. Paper abstract: Today’s consumer virtual reality (VR) systems offer limited haptic feedback via vibration motors in handheld controllers. Rendering haptics to other parts of the body is an open challenge, [...]
Towards Large-scale and Long-term Neural Map Representations
Abstract: We address the problem of large-scale and long-term neural map representations. Maps, as our prior understanding toward the environment, provide valuable information for modern robotics applications such as autonomous driving and AR/VR. The size of maps largely affects the end task performance: usually a more detailed map can support better performance, but would cost [...]