activity
20172023
most citedMAGAN: Margin Adaptation for Generative Adversarial Networks

54 citations · 102 across the 12 of their papers we have counts for

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16 papers · 1 filter

cs.CV20231 cited

High-Fidelity Eye Animatable Neural Radiance Fields for Human Face

Hengfei Wang, Zhongqun Zhang, Yihua Cheng +1

Face rendering using neural radiance fields (NeRF) is a rapidly developing research area in computer vision. While recent methods primarily focus on controlling facial attributes s…

cs.CV2023

BoIR: Box-Supervised Instance Representation for Multi-Person Pose Estimation

Uyoung Jeong, Seungryul Baek, Hyung Jin Chang +1

Single-stage multi-person human pose estimation (MPPE) methods have shown great performance improvements, but existing methods fail to disentangle features by individual instances…

cs.CV20236 cited

Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images

Tze Ho Elden Tse, Franziska Mueller, Zhengyang Shen +8

We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images. Unlike existing hand pose estimation methods, where one typical…

cs.CV2023

Investigation of Architectures and Receptive Fields for Appearance-based Gaze Estimation

Yunhan Wang, Xiangwei Shi, Shalini De Mello +2

With the rapid development of deep learning technology in the past decade, appearance-based gaze estimation has attracted great attention from both computer vision and human-comput…

cs.CV20232 cited

DiffPose: SpatioTemporal Diffusion Model for Video-Based Human Pose Estimation

Runyang Feng, Yixing Gao, Tze Ho Elden Tse +2

Denoising diffusion probabilistic models that were initially proposed for realistic image generation have recently shown success in various perception tasks (e.g., object detection…

cs.CV2023

Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation

Xingyu Zhu, Xin Wang, Jonathan Freer +2

Clothes grasping and unfolding is a core step in robotic-assisted dressing. Most existing works leverage depth images of clothes to train a deep learning-based model to recognize s…