activity
20162026
most citedThe Liver Tumor Segmentation Benchmark (LiTS)

1.2k citations · 2.2k across the 48 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

EvalGIM: A Library for Evaluating Generative Image Models

Melissa Hall, Oscar Mañas, Reyhane Askari-Hemmat +14

As the use of text-to-image generative models increases, so does the adoption of automatic benchmarking methods used in their evaluation. However, while metrics and datasets abound…

cs.CV2024

Boosting Latent Diffusion with Perceptual Objectives

Tariq Berrada, Pietro Astolfi, Melissa Hall +6

Latent diffusion models (LDMs) power state-of-the-art high-resolution generative image models. LDMs learn the data distribution in the latent space of an autoencoder (AE) and produ…

cs.CV2024★ 1 cited

On Improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models

Tariq Berrada Ifriqi, Pietro Astolfi, Melissa Hall +8

Large-scale training of latent diffusion models (LDMs) has enabled unprecedented quality in image generation. However, the key components of the best performing LDM training recipe…

cs.CV2024

Improving Geo-diversity of Generated Images with Contextualized Vendi Score Guidance

Reyhane Askari Hemmat, Melissa Hall, Alicia Sun +3

With the growing popularity of text-to-image generative models, there has been increasing focus on understanding their risks and biases. Recent work has found that state-of-the-art…

cs.CV2024★ 3 cited

Consistency-diversity-realism Pareto fronts of conditional image generative models

Pietro Astolfi, Marlene Careil, Melissa Hall +5

Building world models that accurately and comprehensively represent the real world is the utmost aspiration for conditional image generative models as it would enable their use as…

cs.CV2024★ 1 cited

Towards Geographic Inclusion in the Evaluation of Text-to-Image Models

Melissa Hall, Samuel J. Bell, Candace Ross +3

Rapid progress in text-to-image generative models coupled with their deployment for visual content creation has magnified the importance of thoroughly evaluating their performance…

cs.CV2024★ 6 cited

Improving Text-to-Image Consistency via Automatic Prompt Optimization

Oscar Mañas, Pietro Astolfi, Melissa Hall +6

Impressive advances in text-to-image (T2I) generative models have yielded a plethora of high performing models which are able to generate aesthetically appealing, photorealistic im…