Surface Normal Estimation
39 papers with code • 2 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Surface Normal Estimation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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NYUv2
GRIT
3D Ken Burns Dataset
FutureHouse
Most implemented papers
Human Pose and Shape Estimation from Single Polarization Images
JimmyZou/PolarHumanPoseShape
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This paper focuses on a new problem of estimating human pose and shape from single polarization images.
Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
baegwangbin/surface_normal_uncertainty
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ICCV 2021
Experimental results show that the proposed method outperforms the state-of-the-art in ScanNet and NYUv2, and that the estimated uncertainty correlates well with the prediction error.
Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans
EPFL-VILAB/Omnidata
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ICCV 2021
This paper introduces a pipeline to parametrically sample and render multi-task vision datasets from comprehensive 3D scans from the real world.
Object Pose Estimation using Mid-level Visual Representations
n-nejatishahidin/pose_from_mid-level
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The deep convolutional network models (CNN) for pose estimation are typically trained and evaluated on datasets specifically curated for object detection, pose estimation, or 3D reconstruction, which requires large amounts of training data.
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding
Multi-task dense scene understanding is a thriving research domain that requires simultaneous perception and reasoning on a series of correlated tasks with pixel-wise prediction.
GRIT: General Robust Image Task Benchmark
Computer vision models excel at making predictions when the test distribution closely resembles the training distribution.
Cross-task Attention Mechanism for Dense Multi-task Learning
cv-rits/densemtl
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Multi-task learning has recently become a promising solution for a comprehensive understanding of complex scenes.
Egocentric Scene Understanding via Multimodal Spatial Rectifier
tien-d/EgoDepthNormal
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CVPR 2022
We present a multimodal spatial rectifier that stabilizes the egocentric images to a set of reference directions, which allows learning a coherent visual representation.
Perspective Phase Angle Model for Polarimetric 3D Reconstruction
Current polarimetric 3D reconstruction methods, including those in the well-established shape from polarization literature, are all developed under the orthographic projection assumption.
Multi-Task Meta Learning: learn how to adapt to unseen tasks
ricupa/mtml-learn-how-to-adapt-to-unseen-tasks
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In particular, it focuses simultaneous learning of multiple tasks, an element of MTL and promptly adapting to new tasks, a quality of meta learning.
