Transparent objects

28 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

Segmenting Transparent Object in the Wild with Transformer

xieenze/Trans2Seg 21 Jan 2021

This work presents a new fine-grained transparent object segmentation dataset, termed Trans10K-v2, extending Trans10K-v1, the first large-scale transparent object segmentation dataset.

TOM-Net: Learning Transparent Object Matting from a Single Image

guanyingc/TOM-Net CVPR 2018

In this paper, we first formulate transparent object matting as a refractive flow estimation problem.

Learning Transparent Object Matting

guanyingc/TOM-Net_Rendering 25 Jul 2019

In this paper, we formulate transparent object matting as a refractive flow estimation problem, and propose a deep learning framework, called TOM-Net, for learning the refractive flow.

ClearGrasp: 3D Shape Estimation of Transparent Objects for Manipulation

Shreeyak/cleargrasp 6 Oct 2019

To address these challenges, we present ClearGrasp -- a deep learning approach for estimating accurate 3D geometry of transparent objects from a single RGB-D image for robotic manipulation.

KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects

google-research/google-research CVPR 2020

We address two problems: first, we establish an easy method for capturing and labeling 3D keypoints on desktop objects with an RGB camera; and second, we develop a deep neural network, called $KeyPose$, that learns to accurately predict object poses using 3D keypoints, from stereo input, and works even for transparent objects.

Natural Image Matting via Guided Contextual Attention

Yaoyi-Li/GCA-Matting 13 Jan 2020

Inspired by affinity-based method and the successes of contextual attention in inpainting, we develop a novel end-to-end approach for natural image matting with a guided contextual attention module, which is specifically designed for image matting.

Segmenting Transparent Objects in the Wild

xieenze/Segment_Transparent_Objects ECCV 2020

To address this important problem, this work proposes a large-scale dataset for transparent object segmentation, named Trans10K, consisting of 10, 428 images of real scenarios with carefully manual annotations, which are 10 times larger than the existing datasets.

Through the Looking Glass: Neural 3D Reconstruction of Transparent Shapes

lzqsd/TransparentShapeReconstruction CVPR 2020

Recovering the 3D shape of transparent objects using a small number of unconstrained natural images is an ill-posed problem.

FakeMix Augmentation Improves Transparent Object Detection

yangcao1996/fanet 24 Mar 2021

However, these methods usually encounter boundary-related imbalance problem, leading to limited generation capability.

RGB-D Local Implicit Function for Depth Completion of Transparent Objects

NVlabs/implicit_depth CVPR 2021

Key to our approach is a local implicit neural representation built on ray-voxel pairs that allows our method to generalize to unseen objects and achieve fast inference speed.