8 citations · 8 across the 6 of their papers we have counts for
4 papers · 1 filter
Discovering Latent Graphs with GFlowNets for Diverse Conditional Image Generation
Bailey Trang, Parham Saremi, Alan Q. Wang +6
Capturing diversity is crucial in conditional and prompt-based image generation, particularly when conditions contain uncertainty that can lead to multiple plausible outputs. To ge…
Language-Guided Trajectory Traversal in Disentangled Stable Diffusion Latent Space for Factorized Medical Image Generation
Zahra TehraniNasab, Amar Kumar, Tal Arbel
Text-to-image diffusion models have demonstrated a remarkable ability to generate photorealistic images from natural language prompts. These high-resolution, language-guided synthe…
RL4Med-DDPO: Reinforcement Learning for Controlled Guidance Towards Diverse Medical Image Generation using Vision-Language Foundation Models
Parham Saremi, Amar Kumar, Mohamed Mohamed +2
Vision-Language Foundation Models (VLFM) have shown a tremendous increase in performance in terms of generating high-resolution, photorealistic natural images. While VLFMs show a r…
Toward Reliable Human Pose Forecasting with Uncertainty
Saeed Saadatnejad, Mehrshad Mirmohammadi, Matin Daghyani +6
Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence…