Viewpoint Estimation

16 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

3D Bounding Box Estimation Using Deep Learning and Geometry

smallcorgi/3D-Deepbox 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.

iSPA-Net: Iterative Semantic Pose Alignment Network

val-iisc/iSPA-Net 3 Aug 2018

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

val-iisc/pose_estimation 3 Sep 2018

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 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

YoungXIAO13/PoseFromShape 12 Jun 2019

Most deep pose estimation methods need to be trained for specific object instances or categories.

Self-Supervised Viewpoint Learning From Image Collections

NVlabs/SSV 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 15 Jul 2020

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 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

mbanani/adviser_networks 5 Feb 2018

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?