Geometry-Biased Transformer for Robust Multi-View 3D Human Pose Reconstruction

no code implementations • 28 Dec 2023 • Olivier Moliner, Sangxia Huang, Kalle Åström

We address the challenges in estimating 3D human poses from multiple views under occlusion and with limited overlapping views.

Bootstrapped Representation Learning for Skeleton-Based Action Recognition

no code implementations • 4 Feb 2022 • Olivier Moliner, Sangxia Huang, Kalle Åström

In this work, we study self-supervised representation learning for 3D skeleton-based action recognition.

Action Recognition Data Augmentation +4

Adversarial Attacks and Defences Competition

1 code implementation • 31 Mar 2018 • Alexey Kurakin, Ian Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jian-Yu Wang, Zhishuai Zhang, Zhou Ren, Alan Yuille, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe

To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop new methods to generate adversarial examples as well as to develop new ways to defend against them.

BIG-bench Machine Learning