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Found 5 papers, 2 papers with code
ABO: Dataset and Benchmarks for Real-World 3D Object Understanding
ABO contains product catalog images, metadata, and artist-created 3D models with complex geometries and physically-based materials that correspond to real, household objects.
A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation
The A-Net modifies the original training images constrained by a simplified physical shadow model and is focused on fooling the D-Net's shadow predictions.
Ranked #4 on
Shadow Detection
on SBU
Shadow Detection With Conditional Generative Adversarial Networks
We introduce scGAN, a novel extension of conditional Generative Adversarial Networks (GAN) tailored for the challenging problem of shadow detection in images.
Ranked #6 on
RGB Salient Object Detection
on ISTD
Noisy Label Recovery for Shadow Detection in Unfamiliar Domains
However, shadow detection on broader image domains is still challenging due to the lack of annotated training data.
Leave-One-Out Kernel Optimization for Shadow Detection
Optimizing the leave-one-out cross validation error is typically difficult, but it can be done efficiently in our framework.
