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Found 9 papers, 1 papers with code
Rethinking FID: Towards a Better Evaluation Metric for Image Generation
It is an unbiased estimator that does not make any assumptions on the probability distribution of the embeddings and is sample efficient.
MarkovGen: Structured Prediction for Efficient Text-to-Image Generation
Modern text-to-image generation models produce high-quality images that are both photorealistic and faithful to the text prompts.
Less data is more: Selecting informative and diverse subsets with balancing constraints
Deep learning has yielded extraordinary results in vision and natural language processing, but this achievement comes at a cost.
Balancing Robustness and Sensitivity using Feature Contrastive Learning
It is generally believed that robust training of extremely large networks is critical to their success in real-world applications.
Less is more: Selecting informative and diverse subsets with balancing constraints
Deep learning has yielded extraordinary results in vision and natural language processing, but this achievement comes at a cost.
Understanding Robustness of Transformers for Image Classification
We find that when pre-trained with a sufficient amount of data, ViT models are at least as robust as the ResNet counterparts on a broad range of perturbations.
Toward Perceptually-Consistent Stereo: A Scanline Study
Two types of information exist in a stereo pair: correlation (matching) and decorrelation (half-occlusion).
Hot or Not: Exploring Correlations Between Appearance and Temperature
In this paper we explore interactions between the appearance of an outdoor scene and the ambient temperature.
A Global Approach for Solving Edge-Matching Puzzles
We consider apictorial edge-matching puzzles, in which the goal is to arrange a collection of puzzle pieces with colored edges so that the colors match along the edges of adjacent pieces.
