Transparent objects
28 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Transparent objects
TRansPose
Transparent Object Images | Indoor Object Dataset
Most implemented papers
Segmenting Transparent Object in the Wild with Transformer
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
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CVPR 2018
In this paper, we first formulate transparent object matting as a refractive flow estimation problem.
Learning Transparent Object Matting
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
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
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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
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
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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
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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
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
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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.
