813 citations · 1.2k across the 10 of their papers we have counts for
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Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle +1
Learning-based 3D reconstruction methods have shown impressive results. However, most methods require 3D supervision which is often hard to obtain for real-world datasets. Recently…
Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
Yiyi Liao, Katja Schwarz, Lars Mescheder +1
In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical renderi…
Texture Fields: Learning Texture Representations in Function Space
Michael Oechsle, Lars Mescheder, Michael Niemeyer +2
In recent years, substantial progress has been achieved in learning-based reconstruction of 3D objects. At the same time, generative models were proposed that can generate highly r…