1. [Publications](/publications)
2. FOVI-Dex: Foveation enables efficient perceptive learning of dexterous manipulation in simulation

 # FOVI-Dex: Foveation enables efficient perceptive learning of dexterous manipulation in simulation

  ![Publication image](/sites/default/files/styles/wide/public/default_images/default.jpeg?itok=TfIobf92 "Publication image")

 Advanced physics simulators and rendering engines promise to support the next-generation of robotic reinforcement learning (RL), yet training perceptive policies remains challenging due to the high-costs of rendering and perception. We propose foveation as a solution to this challenge, coupling a novel foveated rendering solution with foveated perception, alongside a careful approach for ensuring transfer to foveated sampling of real uniform cameras. We train a language-conditioned visuotactile policy controlling a dexterous arm-hand to find and grasp a target object in clutter (FOVI-Dex), via online RL without demonstrations. In comparison to a high-resolution fixed-camera control, FOVI-Dex uses 8.9 less vision tokens, supporting 6 more parallel environments and 4.4 higher training throughput. At matched training budgets, this efficiency enables FOVI-Dex to outperform both the high-resolution baseline and a matched uniform active camera baseline, in both sim and real, with an outsized advantage in the real world.

 ## Authors

Nicholas Blauch (NVIDIA)

Nicolas Moënne-Loccoz (NVIDIA)

Jayjun Lee (University of Michigan - Ann Arbor)

Patrick Yin (University of Washington)

Mohak Bhardwaj (NVIDIA)

Muhammad Asif Rana (NVIDIA)

Jessica Yin (NVIDIA)

Sam Mady (NVIDIA)

Karl Van Wyk (NVIDIA)

Nathan D. Ratliff (NVIDIA)

[Jae-Hyun Jung](/person/jae-hyun-jung)

[Ruth Rosenholtz](/person/ruth-rosenholtz)

Ankur Handa (NVIDIA)

Gavriel State (NVIDIA)

 ## Publication Date

Thursday, November 12, 2026

 ## Published in

[Dex-CoRL 2026 Workshop](https://openreview.net/forum?id=Boad839qIT)

 ## Research Area

[Applied Perception](/research-area/applied-perception)

[Artificial Intelligence and Machine Learning ](/research-area/machine-learning-artificial-intelligence)

[Computer Vision](/research-area/computer-vision)

[Machine Translation](/research-area/machine-translation)

[Physical AI](/research-area/physical-ai)

[Robotics](/research-area/robotics)