Results 1 to 10 of about 1,343,632 (346)
Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach
We analyzed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age.
H Andrew Schwartz +2 more
exaly +2 more sources
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models [PDF]
We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies pre-trained text-image diffusion and discriminative models to perform open-vocabulary panoptic segmentation. Text-to-image diffusion models have the remarkable ability
Jiarui Xu +5 more
semanticscholar +1 more source
ISSUES OF STUDENTS MOTIVATION IN FOREIGN LANGUAGE CLASSES [PDF]
Motivation of students plays one of the most important roles in the effective study of a foreign language. If he is not motivated, the student is inattentive in class, does not do homework and may even distract others.
Olena Ye. Beresten +2 more
doaj +1 more source
Side Adapter Network for Open-Vocabulary Semantic Segmentation [PDF]
This paper presents a new framework for open-vocabulary semantic segmentation with the pre-trained vision-language model, named Side Adapter Network (SAN). Our approach models the semantic segmentation task as a region recognition problem. A side network
Mengde Xu +4 more
semanticscholar +1 more source
Scaling Open-Vocabulary Object Detection [PDF]
Open-vocabulary object detection has benefited greatly from pretrained vision-language models, but is still limited by the amount of available detection training data.
M. Minderer, A. Gritsenko, N. Houlsby
semanticscholar +1 more source
OpenMask3D: Open-Vocabulary 3D Instance Segmentation [PDF]
We introduce the task of open-vocabulary 3D instance segmentation. Current approaches for 3D instance segmentation can typically only recognize object categories from a pre-defined closed set of classes that are annotated in the training datasets.
Ayca Takmaz +5 more
semanticscholar +1 more source
Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP [PDF]
Open-vocabulary segmentation is a challenging task requiring segmenting and recognizing objects from an open set of categories. One way to address this challenge is to leverage multi-modal models, such as CLIP, to provide image and text features in a ...
Qihang Yu +4 more
semanticscholar +1 more source
Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP [PDF]
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-stage methods first generate class-agnostic mask proposals and then leverage pre-
Feng Liang +8 more
semanticscholar +1 more source
Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space [PDF]
Transformer-based language models (LMs) are at the core of modern NLP, but their internal prediction construction process is opaque and largely not understood. In this work, we make a substantial step towards unveiling this underlying prediction process,
Mor Geva +3 more
semanticscholar +1 more source
Simple Open-Vocabulary Object Detection with Vision Transformers [PDF]
Combining simple architectures with large-scale pre-training has led to massive improvements in image classification. For object detection, pre-training and scaling approaches are less well established, especially in the long-tailed and open-vocabulary ...
M. Minderer +13 more
semanticscholar +1 more source

