activity
20172026
most citedPeephole: Predicting Network Performance Before Training

84 citations · 97 across the 7 of their papers we have counts for

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8 papers · 1 filter

cs.CV2023

LumiGAN: Unconditional Generation of Relightable 3D Human Faces

Boyang Deng, Yifan Wang, Gordon Wetzstein

Unsupervised learning of 3D human faces from unstructured 2D image data is an active research area. While recent works have achieved an impressive level of photorealism, they commo…

cs.CV2023

GINA-3D: Learning to Generate Implicit Neural Assets in the Wild

Bokui Shen, Xinchen Yan, Charles R. Qi +5

Modeling the 3D world from sensor data for simulation is a scalable way of developing testing and validation environments for robotic learning problems such as autonomous driving.…

cs.CV2021

Offboard 3D Object Detection from Point Cloud Sequences

Charles R. Qi, Yin Zhou, Mahyar Najibi +4

While current 3D object recognition research mostly focuses on the real-time, onboard scenario, there are many offboard use cases of perception that are largely under-explored, suc…

cs.CV20205 cited

NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis

Pratul P. Srinivasan, Boyang Deng, Xiuming Zhang +3

We present a method that takes as input a set of images of a scene illuminated by unconstrained known lighting, and produces as output a 3D representation that can be rendered from…

cs.CV2019

CvxNet: Learnable Convex Decomposition

Boyang Deng, Kyle Genova, Soroosh Yazdani +3

Any solid object can be decomposed into a collection of convex polytopes (in short, convexes). When a small number of convexes are used, such a decomposition can be thought of as a…

cs.CV20196 cited

Cerberus: A Multi-headed Derenderer

Boyang Deng, Simon Kornblith, Geoffrey Hinton

To generalize to novel visual scenes with new viewpoints and new object poses, a visual system needs representations of the shapes of the parts of an object that are invariant to c…