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Found 3 papers, 3 papers with code
DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image
Experimentally, DAD-3DNet outperforms or is comparable to the state-of-the-art models in (i) 3D Head Pose Estimation on AFLW2000-3D and BIWI, (ii) 3D Face Shape Reconstruction on NoW and Feng, and (iii) 3D Dense Head Alignment and 3D Landmarks Estimation on DAD-3DHeads dataset.
Ranked #6 on
Head Pose Estimation
on AFLW2000
FEAR: Fast, Efficient, Accurate and Robust Visual Tracker
In addition, we expand the definition of the model efficiency by introducing FEAR benchmark that assesses energy consumption and execution speed.
Ranked #22 on
Visual Object Tracking
on GOT-10k
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
We present a new end-to-end generative adversarial network (GAN) for single image motion deblurring, named DeblurGAN-v2, which considerably boosts state-of-the-art deblurring efficiency, quality, and flexibility.
Ranked #3 on
Blind Face Restoration
on CelebA-Test
