Papers with Code 아카이브

Viewpoint Estimation

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Holmes-Alan/See360

공식 코드

See360: Novel Panoramic View Interpolation

https://github.com/NVlabs/SSV

공식 코드

Self-Supervised Viewpoint Learning From Image Collections

https://github.com/Spandan-Madan/generalization_biased_category_pose

공식 코드

When and how CNNs generalize to out-of-distribution category-viewpoint combinations

https://github.com/YoungXIAO13/PoseContrast

공식 코드

PoseContrast: Class-Agnostic Object Viewpoint Estimation in the Wild with Pose-Aware Contrastive Learning

https://github.com/lemmersj/ground-truth-or-daer

공식 코드

Ground-truth or DAER: Selective Re-query of Secondary Information

https://github.com/leoshine/Spherical_Regression

공식 코드

Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres

https://github.com/mbanani/novelviewpoints

공식 코드

Novel Object Viewpoint Estimation through Reconstruction Alignment

https://github.com/val-iisc/iSPA-Net

공식 코드

iSPA-Net: Iterative Semantic Pose Alignment Network

https://github.com/val-iisc/pose_estimation

공식 코드

Object Pose Estimation from Monocular Image using Multi-View Keypoint Correspondence

https://github.com/xingyizhou/StarMap

공식 코드

StarMap for Category-Agnostic Keypoint and Viewpoint Estimation

https://github.com/ConnorChristie/image-to-3d-bbox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/QUVA-Lab/Spherical_Regression

Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres

https://github.com/ShapeNet/RenderForCNN

Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views

https://github.com/YoungXIAO13/FewShotDetection

Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild

https://github.com/YoungXIAO13/PoseFromShape

Pose from Shape: Deep Pose Estimation for Arbitrary 3D Objects

https://github.com/ZhixinLai/3D-detection-with-monocular-RGB-image

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/aniketpokale10/RenderForCNN_modified

Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views

https://github.com/cersar/3D_detection

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/fuenwang/3D-BoundingBox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/lzccccc/3d-bounding-box-estimation-for-autonomous-driving

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/m-parchami/3DVehicleDetection

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/mbanani/adviser_networks

Adviser Networks: Learning What Question to Ask for Human-In-The-Loop Viewpoint Estimation

https://github.com/mees/self-supervised-3D

Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics

https://github.com/ruhyadi/YOLO3D

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/ruhyadi/yolo3d-lightning

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/sarthaksharma13/RenderForCNN_KeypointGeneration

Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views

https://github.com/sarthaksharma13/RenderForCNN_annotation

Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views

https://github.com/sebamenabar/SPACE-Pytorch-Implementation

Self-Supervised Viewpoint Learning From Image Collections

https://github.com/skhadem/3D-BoundingBox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/smallcorgi/3D-Deepbox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/spandan-madan/in_distribution_adversarial_examples

When and how CNNs generalize to out-of-distribution category-viewpoint combinations

https://github.com/wittmaan/a2d2

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/xingyuansun/pix3d

Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.