Vision-language pre-training: Basics, recent advances, and future trends
This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …
intelligence that have been developed in the last few years. We group these approaches …
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 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 …
Open-vocabulary panoptic segmentation with text-to-image diffusion models
We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies
pre-trained text-image diffusion and discriminative models to perform open-vocabulary …
pre-trained text-image diffusion and discriminative models to perform open-vocabulary …
Lerf: Language embedded radiance fields
Humans describe the physical world using natural language to refer to specific 3D locations
based on a vast range of properties: visual appearance, semantics, abstract associations, or …
based on a vast range of properties: visual appearance, semantics, abstract associations, or …
Open-vocabulary semantic segmentation with mask-adapted clip
Open-vocabulary semantic segmentation aims to segment an image into semantic regions
according to text descriptions, which may not have been seen during training. Recent two …
according to text descriptions, which may not have been seen during training. Recent two …
Groupvit: Semantic segmentation emerges from text supervision
Grouping and recognition are important components of visual scene understanding, eg, for
object detection and semantic segmentation. With end-to-end deep learning systems …
object detection and semantic segmentation. With end-to-end deep learning systems …
Generalized decoding for pixel, image, and language
We present X-Decoder, a generalized decoding model that can predict pixel-level
segmentation and language tokens seamlessly. X-Decoder takes as input two types of …
segmentation and language tokens seamlessly. X-Decoder takes as input two types of …
Rt-2: Vision-language-action models transfer web knowledge to robotic control
A Brohan, N Brown, J Carbajal, Y Chebotar… - arXiv preprint arXiv …, 2023 - arxiv.org
We study how vision-language models trained on Internet-scale data can be incorporated
directly into end-to-end robotic control to boost generalization and enable emergent …
directly into end-to-end robotic control to boost generalization and enable emergent …
Detecting twenty-thousand classes using image-level supervision
Current object detectors are limited in vocabulary size due to the small scale of detection
datasets. Image classifiers, on the other hand, reason about much larger vocabularies, as …
datasets. Image classifiers, on the other hand, reason about much larger vocabularies, as …