4 papers
PLACID: Identity-Preserving Multi-Object Compositing via Video Diffusion with Synthetic Trajectories
Gemma Canet Tarrés, Manel Baradad, Francesc Moreno-Noguer +1
Recent advances in generative AI have dramatically improved photorealistic image synthesis, yet they fall short for studio-level multi-object compositing. This task demands simulta…
Cost Savings from Automatic Quality Assessment of Generated Images
Xavier Giro-i-Nieto, Nefeli Andreou, Anqi Liang +3
Deep generative models have shown impressive progress in recent years, making it possible to produce high quality images with a simple text prompt or a reference image. However, st…
Separating Knowledge and Perception with Procedural Data
Adrián RodrÃguez-Muñoz, Manel Baradad, Phillip Isola +1
We train representation models with procedural data only, and apply them on visual similarity, classification, and semantic segmentation tasks without further training by using vis…
Deep Augmentation: Dropout as Augmentation for Self-Supervised Learning
Rickard Brüel-Gabrielsson, Tongzhou Wang, Manel Baradad +1
Despite dropout's ubiquity in machine learning, its effectiveness as a form of data augmentation remains under-explored. We address two key questions: (i) When is dropout effective…