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Numfor Mbiziwo-Tiapo

2 accepted papers

2026

Emergent Dexterity Via Diverse Resets and Large-Scale Reinforcement Learning

ICLR 2026poster

Reinforcement learning in GPU-enabled physics simulation has been the driving force behind many of the breakthroughs in sim-to-real robot learning. However, current approaches for data generation in simulation are unwieldy and task-specific, requiring extensive human effort to engineer training curr…

Cited by 0SourceScholar
2025

DRAWER: Digital Reconstruction and Articulation With Environment Realism

CVPR 2025poster

Creating virtual digital replicas from real-world data unlocks significant potential across domains like gaming and robotics. In this paper, we present DRAWER, a novel framework that converts a video of a static indoor scene into a photorealistic and interactive digital environment. Our approach cen…