Search Results for author:
Found 5 papers, 4 papers with code
EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields
We present EvDNeRF, a pipeline for generating event data and training an event-based dynamic NeRF, for the purpose of faithfully reconstructing eventstreams on scenes with rigid and non-rigid deformations that may be too fast to capture with a standard camera.
Is Imitation All You Need? Generalized Decision-Making with Dual-Phase Training
We introduce DualMind, a generalist agent designed to tackle various decision-making tasks that addresses challenges posed by current methods, such as overfitting behaviors and dependence on task-specific fine-tuning.
SMART: Self-supervised Multi-task pretrAining with contRol Transformers
Self-supervised pretraining has been extensively studied in language and vision domains, where a unified model can be easily adapted to various downstream tasks by pretraining representations without explicit labels.
AirSim Drone Racing Lab
Autonomous drone racing is a challenging research problem at the intersection of computer vision, planning, state estimation, and control.
Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations
We analyze the rich latent spaces learned with our proposed representations, and show that the use of our cross-modal architecture significantly improves control policy performance as compared to end-to-end learning or purely unsupervised feature extractors.
