#diffusion models
115 papers · 1 filter
When Pretty Isn't Useful: Investigating Why Modern Text-to-Image Models Fail as Reliable Training Data Generators
Krzysztof Adamkiewicz, Brian Bernhard Moser, Stanislav Frolov +3
The paper evaluates modern text-to-image diffusion models as sources of synthetic training data and finds that, despite higher visual quality, newer models produce less diverse ima…
CoDi -- an exemplar-conditioned diffusion model for low-shot counting
Grega Å uÅ¡tar, Jer Pelhan, Alan LukežiÄ +1
CoDi is a latent diffusion-based model that uses exemplar-conditioned conditioning to generate high-quality density maps for low-shot object counting, enabling accurate object loca…
RePlan: Reasoning-guided Region Planning for Complex Instruction-based Image Editing
Tianyuan Qu, Lei Ke, Xiaohang Zhan +6
The paper presents RePlan, a framework that first reasons about natural‑language instructions to identify specific image regions and then edits those regions using a diffusion mode…
WorldWander: Bridging Egocentric and Exocentric Worlds in Video Generation
Quanjian Song, Yiren Song, Kelly Peng +2
WorldWander is a framework that translates video content between first‑person (egocentric) and third‑person (exocentric) views using video diffusion transformers and in‑context lea…
Integration Matters: Rollout-Based Training for Constrained Diffusion Models
Xiaoxuan Liang, Saeid Naderiparizi, Berend Zwartsenberg +1
The paper introduces a fine‑tuning method that uses online rollout to guide constraint enforcement during training of diffusion models, aligning training with the sampling process…
From Vector Autoregressions to AI-based Time Series Forecasting: A Review
Likai Chen, Weining Wang
The paper reviews recent AI-driven time‑series forecasting methods—including transformers, large pretrained zero‑shot models, and diffusion‑based forecasters—and relates them to tr…