4 papers
Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis
Keerthi Kaashyap, Dennis Anthony, Akshay Krishnan +5
This paper examines the role of Novel View Synthesis (NVS) in geometric representation learning. In principle, NVS should reason about 3D scene structure, thereby enabling transfer…
Cross-View Splatter: Feed-Forward View Synthesis with Georeferenced Images
Matias Turkulainen, Akshay Krishnan, Filippo Aleotti +6
We present Cross-View Splatter, a feed-forward method that predicts pixel-aligned Gaussian splats for outdoor scenes captured at ground level AND by satellite. Faithful reconstruct…
Orchid: Image Latent Diffusion for Joint Appearance and Geometry Generation
Akshay Krishnan, Xinchen Yan, Vincent Casser +1
We introduce Orchid, a unified latent diffusion model that learns a joint appearance-geometry prior to generate color, depth, and surface normal images in a single diffusion proces…
OmniNOCS: A unified NOCS dataset and model for 3D lifting of 2D objects
Akshay Krishnan, Abhijit Kundu, Kevis-Kokitsi Maninis +2
We propose OmniNOCS, a large-scale monocular dataset with 3D Normalized Object Coordinate Space (NOCS) maps, object masks, and 3D bounding box annotations for indoor and outdoor sc…