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20182022
most citedCogradient Descent for Bilinear Optimization

5 citations · 8 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CV20223 cited

UV-Based 3D Hand-Object Reconstruction with Grasp Optimization

Ziwei Yu, Linlin Yang, You Xie +2

We propose a novel framework for 3D hand shape reconstruction and hand-object grasp optimization from a single RGB image. The representation of hand-object contact regions is criti…

cs.CV20205 cited

Cogradient Descent for Bilinear Optimization

Li'an Zhuo, Baochang Zhang, Linlin Yang +5

Conventional learning methods simplify the bilinear model by regarding two intrinsically coupled factors independently, which degrades the optimization procedure. One reason lies i…

cs.CV2020

CP-NAS: Child-Parent Neural Architecture Search for Binary Neural Networks

Li'an Zhuo, Baochang Zhang, Hanlin Chen +4

Neural architecture search (NAS) proves to be among the best approaches for many tasks by generating an application-adaptive neural architecture, which is still challenged by high…

cs.CV2020

Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction

Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek +32

We study how well different types of approaches generalise in the task of 3D hand pose estimation under single hand scenarios and hand-object interaction. We show that the accuracy…

cs.CV2018

Disentangling Latent Hands for Image Synthesis and Pose Estimation

Linlin Yang, Angela Yao

Hand image synthesis and pose estimation from RGB images are both highly challenging tasks due to the large discrepancy between factors of variation ranging from image background c…