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Found 7 papers, 2 papers with code
Improving Robustness for Pose Estimation via Stable Heatmap Regression
Deep learning methods have achieved excellent performance in pose estimation, but the lack of robustness causes the keypoints to change drastically between similar images.
Switching Transferable Gradient Directions for Query-Efficient Black-Box Adversarial Attacks
In each iteration, SWITCH first tries to update the current sample along the direction of $\hat{\mathbf{g}}$, but considers switching to its opposite direction $-\hat{\mathbf{g}}$ if our algorithm detects that it does not increase the value of the attack objective function.
Self-Paced Video Data Augmentation with Dynamic Images Generated by Generative Adversarial Networks
The dynamic image compresses the motion information of video into a still image, removing the interference factors such as the background.
Adaptive Wasserstein Hourglass for Weakly Supervised Hand Pose Estimation from Monocular RGB
During training, based on the relation between these common characteristics and 3D pose learned from fully-annotated synthetic datasets, it is beneficial for the network to restore the 3D pose of weakly labeled real-world datasets with the aid of 2D annotations and depth images.
MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks
To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples.
DenseAttentionSeg: Segment Hands from Interacted Objects Using Depth Input
We propose a real-time DNN-based technique to segment hand and object of interacting motions from depth inputs.
AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection
(2) We integrate various dynamic models (including convolutional long short-term memory, two stream network, conditional random field, and temporal action localization network) into AU R-CNN and then investigate and analyze the reason behind the performance of dynamic models.
Ranked #1 on
Action Unit Detection
on BP4D
