Paper Reading AI Learner

Reconstruct, Rasterize and Backprop: Dense shape and pose estimation from a single image

2020-04-25 20:53:43
Aniket Pokale, Aditya Aggarwal, K. Madhava Krishna

Abstract

This paper presents a new system to obtain dense object reconstructions along with 6-DoF poses from a single image. Geared towards high fidelity reconstruction, several recent approaches leverage implicit surface representations and deep neural networks to estimate a 3D mesh of an object, given a single image. However, all such approaches recover only the shape of an object; the reconstruction is often in a canonical frame, unsuitable for downstream robotics tasks. To this end, we leverage recent advances in differentiable rendering (in particular, rasterization) to close the loop with 3D reconstruction in camera frame. We demonstrate that our approach---dubbed reconstruct, rasterize and backprop (RRB) achieves significantly lower pose estimation errors compared to prior art, and is able to recover dense object shapes and poses from imagery. We further extend our results to an (offline) setup, where we demonstrate a dense monocular object-centric egomotion estimation system.

Abstract (translated)

URL

https://arxiv.org/abs/2004.12232

PDF

https://arxiv.org/pdf/2004.12232.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot