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Found 7 papers, 4 papers with code
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation
In this work, we propose to fuse the scene reconstruction from multiple images and distill this knowledge into a more accurate single-view scene reconstruction.
ControlRoom3D: Room Generation using Semantic Proxy Rooms
Central to our approach is a user-defined 3D semantic proxy room that outlines a rough room layout based on semantic bounding boxes and a textual description of the overall room style.
Cache Me if You Can: Accelerating Diffusion Models through Block Caching
However, one of the major drawbacks of diffusion models is that the image generation process is costly.
S4C: Self-Supervised Semantic Scene Completion with Neural Fields
3D semantic scene understanding is a fundamental challenge in computer vision.
Behind the Scenes: Density Fields for Single View Reconstruction
By directly sampling color from the available views instead of storing color in the density field, our scene representation becomes significantly less complex compared to NeRFs, and a neural network can predict it in a single forward pass.
De-rendering 3D Objects in the Wild
With increasing focus on augmented and virtual reality applications (XR) comes the demand for algorithms that can lift objects from images and videos into representations that are suitable for a wide variety of related 3D tasks.
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera
Unlike other multi-view stereo methods, MonoRec is able to reconstruct both static and moving objects by leveraging the predicted masks.
