This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality
Assessment (S-UGC VQA) where various excellent solutions are submitted and evaluated …

Recommender systems have become a popular and effective means to manage the ever-
increasing amount of multimedia content available today and to help users discover …

Contrastive models like CLIP have been shown to learn robust representations of images
that capture both semantics and style. To leverage these representations for image …

Transformers have recently gained significant attention in the computer vision community.
However, the lack of scalability of self-attention mechanisms with respect to image size has …

We introduce a novel sequential modeling approach which enables learning a Large Vision
Model (LVM) without making use of any linguistic data. To do this we define a common …

Measuring the perception of visual content is a long-standing problem in computer vision.
Many mathematical models have been developed to evaluate the look or quality of an …

Well-designed prompts can guide text-to-image models to generate amazing images.
However, the performant prompts are often model-specific and misaligned with user input …

Text-guided image editing can have a transformative impact in supporting creative
applications. A key challenge is to generate edits that are faithful to the input text prompt …

Image quality assessment (IQA) is an important research topic for understanding and
improving visual experience. The current state-of-the-art IQA methods are based on …

Foundation models are first pre-trained on vast unsupervised datasets and then fine-tuned
on labeled data. Reinforcement learning, notably from human feedback (RLHF), can further …