Mean-Field methods for Structured Deep-Learning in Computer Vision

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In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

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Mean-Field methods for Structured Deep-Learning in Computer Vision

Chat with Graph Search

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

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Incorporating Projective Geometry into Deep Learning

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Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

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Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Towards Trustworthy Deep Learning for Image Reconstruction

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A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (1/6)

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms