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Found 6 papers, 1 papers with code
POSTURE: Pose Guided Unsupervised Domain Adaptation for Human Body Part Segmentation
Existing algorithms for human body part segmentation have shown promising results on challenging datasets, primarily relying on end-to-end supervision.
STRIDE: Single-video based Temporally Continuous Occlusion Robust 3D Pose Estimation
This challenge arises because these models struggle to generalize beyond their training datasets, and the variety of occlusions is hard to capture in the training data.
Learning Deformable 3D Graph Similarity to Track Plant Cells in Unregistered Time Lapse Images
Tracking of plant cells in images obtained by microscope is a challenging problem due to biological phenomena such as large number of cells, non-uniform growth of different layers of the tightly packed plant cells and cell division.
Prior-guided Source-free Domain Adaptation for Human Pose Estimation
To address this limitation, we focus on the task of source-free domain adaptation for pose estimation, where a source model must adapt to a new target domain using only unlabeled target data.
GAMA: Generative Adversarial Multi-Object Scene Attacks
Using the joint image-text features to train the generator, we show that GAMA can craft potent transferable perturbations in order to fool victim classifiers in various attack settings.
Poisson2Sparse: Self-Supervised Poisson Denoising From a Single Image
In this work, we explore a sparsity and dictionary learning-based approach and present a novel self-supervised learning method for single-image denoising where the noise is approximated as a Poisson process, requiring no clean ground-truth data.
