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Found 11 papers, 5 papers with code
Depth Pro: Sharp Monocular Metric Depth in Less Than a Second
We present a foundation model for zero-shot metric monocular depth estimation.
Unsupervised Contrastive Domain Adaptation for Semantic Segmentation
Semantic segmentation models struggle to generalize in the presence of domain shift.
Dancing under the stars: video denoising in starlight
To enable this, we develop a GAN-tuned physics-based noise model to more accurately represent camera noise at the lowest light levels.
Ranked #7 on
Image Denoising
on SID x300
DeepMesh: Differentiable Iso-Surface Extraction
Our key insight is that by reasoning on how implicit field perturbations impact local surface geometry, one can ultimately differentiate the 3D location of surface samples with respect to the underlying deep implicit field.
Enhancing Photorealism Enhancement
We confirm the benefits of our contributions in controlled experiments and report substantial gains in stability and realism in comparison to recent image-to-image translation methods and a variety of other baselines.
MeshSDF: Differentiable Iso-Surface Extraction
Unfortunately, these methods are often not suitable for applications that require an explicit mesh-based surface representation because converting an implicit field to such a representation relies on the Marching Cubes algorithm, which cannot be differentiated with respect to the underlying implicit field.
What Do Single-view 3D Reconstruction Networks Learn?
Convolutional networks for single-view object reconstruction have shown impressive performance and have become a popular subject of research.
Ranked #1 on
3D Reconstruction
on 300W
Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers
We scale this baseline to higher resolutions by proposing a memory-efficient shape encoding, which recursively decomposes a 3D shape into nested shape layers, similar to the pieces of a Matryoshka doll.
Ranked #6 on
3D Object Reconstruction
on Data3D−R2N2
Playing for Data: Ground Truth from Computer Games
Recent progress in computer vision has been driven by high-capacity models trained on large datasets.
Discriminative Shape From Shading in Uncalibrated Illumination
Von Mises-Fisher distributions in the leaves of each tree enable the estimation of surface normals.
