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20222024
most citedSynthetic Data in Human Analysis: A Survey

16 citations · 20 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

GHNeRF: Learning Generalizable Human Features with Efficient Neural Radiance Fields

Arnab Dey, Di Yang, Rohith Agaram +4

Recent advances in Neural Radiance Fields (NeRF) have demonstrated promising results in 3D scene representations, including 3D human representations. However, these representations…

cs.CV2024

HFNeRF: Learning Human Biomechanic Features with Neural Radiance Fields

Arnab Dey, Di Yang, Antitza Dantcheva +1

In recent advancements in novel view synthesis, generalizable Neural Radiance Fields (NeRF) based methods applied to human subjects have shown remarkable results in generating nove…

cs.CV2023

Self-Supervised Video Representation Learning via Latent Time Navigation

Di Yang, Yaohui Wang, Quan Kong +4

Self-supervised video representation learning aimed at maximizing similarity between different temporal segments of one video, in order to enforce feature persistence over time. Th…

cs.CV20224 cited

ViA: View-invariant Skeleton Action Representation Learning via Motion Retargeting

Di Yang, Yaohui Wang, Antitza Dantcheva +3

Current self-supervised approaches for skeleton action representation learning often focus on constrained scenarios, where videos and skeleton data are recorded in laboratory setti…

cs.CV202216 cited

Synthetic Data in Human Analysis: A Survey

Indu Joshi, Marcel Grimmer, Christian Rathgeb +3

Deep neural networks have become prevalent in human analysis, boosting the performance of applications, such as biometric recognition, action recognition, as well as person re-iden…