Surface Normals Estimation
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Benchmarks
PCPNet
Stanford-ORB
NYU Depth v2
ScanNetV2
IBims-1
PASCAL Context
Taskonomy
Most implemented
BlenderProc
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
iDisc: Internal Discretization for Monocular Depth Estimation
Extracting Triangular 3D Models, Materials, and Lighting From Images
$360^o$ Surface Regression with a Hyper-Sphere Loss
Deep Iterative Surface Normal Estimation
Papers
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
Monocular depth estimation is a ubiquitous yet highly ill-posed computer vision task, with downstream applications in scene reconstruction, computational photography, and robotics, among others. Despite the field's matur…
Surface Normals EstimationMonocular Depth EstimationImage GenerationLearning from the Giants: A Practical Approach to Underwater Depth and Surface Normals Estimation
Monocular Depth and Surface Normals Estimation (MDSNE) is crucial for tasks such as 3D reconstruction, autonomous navigation, and underwater exploration. Current methods rely either on discriminative models, which strugg…
3D ReconstructionAutonomous NavigationAutonomous VehiclesSurface Normals EstimationFine-Tuning Image-Conditional Diffusion Models is Easier than You Think
Recent work showed that large diffusion models can be reused as highly precise monocular depth estimators by casting depth estimation as an image-conditional image generation task. While the proposed model achieved state…
Conditional Image GenerationDepth EstimationImage GenerationMonocular Depth Estimation+2PolyMaX: General Dense Prediction with Mask Transformer
Dense prediction tasks, such as semantic segmentation, depth estimation, and surface normal prediction, can be easily formulated as per-pixel classification (discrete outputs) or regression (continuous outputs). This per…
Depth EstimationMonocular Depth EstimationPredictionSemantic Segmentation+2Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark
We introduce Stanford-ORB, a new real-world 3D Object inverse Rendering Benchmark. Recent advances in inverse rendering have enabled a wide range of real-world applications in 3D content generation, moving rapidly from r…
Depth PredictionImage RelightingInverse RenderingObject+2Large-scale Monocular Depth Estimation in the Wild
Estimating the relative depth of a single image (Monocular Depth Estimation) is a significant step towards understanding the general structure of the depicted scenery, the relations of entities in the scene and their int…
Depth EstimationDepth PredictionMonocular Depth EstimationSurface Normal Estimation+1