[HTML][HTML] Review of large vision models and visual prompt engineering
Visual prompt engineering is a fundamental methodology in the field of visual and image
artificial general intelligence. As the development of large vision models progresses, the …
artificial general intelligence. As the development of large vision models progresses, the …
A comprehensive survey on segment anything model for vision and beyond
Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …
Segment anything
Abstract We introduce the Segment Anything (SA) project: a new task, model, and dataset for
image segmentation. Using our efficient model in a data collection loop, we built the largest …
image segmentation. Using our efficient model in a data collection loop, we built the largest …
Adding conditional control to text-to-image diffusion models
L Zhang, A Rao, M Agrawala - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
We present ControlNet, a neural network architecture to add spatial conditioning controls to
large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large …
large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large …
Segment everything everywhere all at once
In this work, we present SEEM, a promotable and interactive model for segmenting
everything everywhere all at once in an image. In SEEM, we propose a novel and versatile …
everything everywhere all at once in an image. In SEEM, we propose a novel and versatile …
Depth anything: Unleashing the power of large-scale unlabeled data
Abstract This work presents Depth Anything a highly practical solution for robust monocular
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
Convolutions die hard: Open-vocabulary segmentation with single frozen convolutional clip
Open-vocabulary segmentation is a challenging task requiring segmenting and recognizing
objects from an open set of categories in diverse environments. One way to address this …
objects from an open set of categories in diverse environments. One way to address this …
Mask dino: Towards a unified transformer-based framework for object detection and segmentation
In this paper we present Mask DINO, a unified object detection and segmentation
framework. Mask DINO extends DINO (DETR with Improved Denoising Anchor Boxes) by …
framework. Mask DINO extends DINO (DETR with Improved Denoising Anchor Boxes) by …
A simple framework for open-vocabulary segmentation and detection
In this work, we present OpenSeeD, a simple Open-vocabulary Segmentation and Detection
framework that learns from different segmentation and detection datasets. To bridge the gap …
framework that learns from different segmentation and detection datasets. To bridge the gap …
Multimodal foundation models: From specialists to general-purpose assistants
Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …
methods to data compression. Recent advances in statistical machine learning have opened …