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Found 4 papers, 2 papers with code
Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions
We call the aggregate of these contribution maps the Implicit Neural Canvas and we use this concept to demonstrate that the INRs which we study learn to ''see'' the frames they represent in surprising ways.
Do text-free diffusion models learn discriminative visual representations?
We find that the intermediate feature maps of the U-Net are diverse, discriminative feature representations.
Diffusion Models Beat GANs on Image Classification
We explore optimal methods for extracting and using these embeddings for classification tasks, demonstrating promising results on the ImageNet classification task.
Leveraging Bitstream Metadata for Fast, Accurate, Generalized Compressed Video Quality Enhancement
Video compression is a central feature of the modern internet powering technologies from social media to video conferencing.
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