Diffuse Attend and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

J Tian, L Aggarwal, A Colaco, Z Kira… - Proceedings of the …, 2024 - openaccess.thecvf.com
Producing quality segmentation masks for images is a fundamental problem in computer
vision. Recent research has explored large-scale supervised training to enable zero-shot …

Exploring Phrase-Level Grounding with Text-to-Image Diffusion Model

D Yang, R Dong, J Ji, Y Ma, H Wang, X Sun… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, diffusion models have increasingly demonstrated their capabilities in vision
understanding. By leveraging prompt-based learning to construct sentences, these models …

MaskDiffusion: Exploiting Pre-trained Diffusion Models for Semantic Segmentation

Y Kawano, Y Aoki - arXiv preprint arXiv:2403.11194, 2024 - arxiv.org
Semantic segmentation is essential in computer vision for various applications, yet
traditional approaches face significant challenges, including the high cost of annotation and …

HaVTR: Improving Video-Text Retrieval Through Augmentation Using Large Foundation Models

Y Wang, S Yuan, X Jian, W Pang, M Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
While recent progress in video-text retrieval has been driven by the exploration of powerful
model architectures and training strategies, the representation learning ability of video-text …