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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…
Unlocking Pre-trained Image Backbones for Semantic Image Synthesis
Tariq Berrada, Jakob Verbeek, Camille Couprie +1
Semantic image synthesis, i.e., generating images from user-provided semantic label maps, is an important conditional image generation task as it allows to control both the content…
Guided Distillation for Semi-Supervised Instance Segmentation
Tariq Berrada, Camille Couprie, Karteek Alahari +1
Although instance segmentation methods have improved considerably, the dominant paradigm is to rely on fully-annotated training images, which are tedious to obtain. To alleviate th…