Viewpoint Estimation
17 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Viewpoint Estimation
PASCAL3D+
Most implemented papers
3D Bounding Box Estimation Using Deep Learning and Geometry
smallcorgi/3D-Deepbox
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CVPR 2017
In contrast to current techniques that only regress the 3D orientation of an object, our method first regresses relatively stable 3D object properties using a deep convolutional neural network and then combines these estimates with geometric constraints provided by a 2D object bounding box to produce a complete 3D bounding box.
Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views
Object viewpoint estimation from 2D images is an essential task in computer vision.
iSPA-Net: Iterative Semantic Pose Alignment Network
Such image comparison based approach also alleviates the problem of data scarcity and hence enhances scalability of the proposed approach for novel object categories with minimal annotation.
Object Pose Estimation from Monocular Image using Multi-View Keypoint Correspondence
In this work, we propose a data-efficient method which utilizes the geometric regularity of intraclass objects for pose estimation.
Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres
leoshine/Spherical_Regression
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CVPR 2019
We observe many continuous output problems in computer vision are naturally contained in closed geometrical manifolds, like the Euler angles in viewpoint estimation or the normals in surface normal estimation.
Pose from Shape: Deep Pose Estimation for Arbitrary 3D Objects
Most deep pose estimation methods need to be trained for specific object instances or categories.
Self-Supervised Viewpoint Learning From Image Collections
NVlabs/SSV
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CVPR 2020
Training deep neural networks to estimate the viewpoint of objects requires large labeled training datasets.
When and how CNNs generalize to out-of-distribution category-viewpoint combinations
Spandan-Madan/generalization_biased_category_pose
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In this paper, we investigate when and how such OOD generalization may be possible by evaluating CNNs trained to classify both object category and 3D viewpoint on OOD combinations, and identifying the neural mechanisms that facilitate such OOD generalization.
Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild
YoungXIAO13/FewShotDetection
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ECCV 2020
In this paper, we tackle the problems of few-shot object detection and few-shot viewpoint estimation.
Adviser Networks: Learning What Question to Ask for Human-In-The-Loop Viewpoint Estimation
We address this question by formulating it as an Adviser Problem: can we learn a mapping from the input to a specific question to ask the human to maximize the expected positive impact to the overall task?
