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Rohith Agaram

2 accepted papers

2023

Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields

CVPR 2023highlight

Coordinate-based implicit neural networks, or neural fields, have emerged as useful representations of shape and appearance in 3D computer vision. Despite advances however, it remains challenging to build neural fields for categories of objects without datasets like ShapeNet that provide "canonicali…

2023

HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork

NeurIPS 2023poster

Neural Radiance Fields (NeRF) have become an increasingly popular representation to capture high-quality appearance and shape of scenes and objects. However, learning generalizable NeRF priors over categories of scenes or objects has been challenging due to the high dimensionality of network weight…

Cited by 13SourcePDFScholar