Large foundation models, including large language models (LLMs), vision transformers
(ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine …

Diffusion models represent a new paradigm in text-to-image generation. Beyond generating
high-quality images from text prompts models such as Stable Diffusion have been …

Diffusion models (DMs) have gained prominence due to their ability to generate high-quality,
varied images, with recent advancements in text-to-image generation. The research focus is …

Recent studies have highlighted biases in generative models, shedding light on their
predisposition towards gender-based stereotypes and imbalances. This paper contributes to …

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation
capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image …

Recently, diffusion models have increasingly demonstrated their capabilities in vision
understanding. By leveraging prompt-based learning to construct sentences, these models …

In this paper, we explore the visual representations produced from a pre-trained text-to-
video (T2V) diffusion model for video understanding tasks. We hypothesize that the latent …

While many unsupervised learning models focus on one family of tasks, either generative or
discriminative, we explore the possibility of a unified representation learner: a model which …

We introduce InVi, an approach for inserting or replacing objects within videos (referred to
as inpainting) using off-the-shelf, text-to-image latent diffusion models. InVi targets controlled …

We propose an end-to-end approach for gaze target detection: predicting a head-target
connection between individuals and the target image regions they are looking at. Most of the …