518 citations · 810 across the 5 of their papers we have counts for
6 papers
PaLI-X: On Scaling up a Multilingual Vision and Language Model
Xi Chen, Josip Djolonga, Piotr Padlewski +40
We present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training t…
PaLI: A Jointly-Scaled Multilingual Language-Image Model
Xi Chen, Xiao Wang, Soravit Changpinyo +26
Effective scaling and a flexible task interface enable large language models to excel at many tasks. We present PaLI (Pathways Language and Image model), a model that extends this…
CoCa: Contrastive Captioners are Image-Text Foundation Models
Jiahui Yu, Zirui Wang, Vijay Vasudevan +3
Exploring large-scale pretrained foundation models is of significant interest in computer vision because these models can be quickly transferred to many downstream tasks. This pape…
Image Segmentation Using Hierarchical Merge Tree
Ting Liu, Mojtaba Seyedhosseini, Tolga Tasdizen
This paper investigates one of the most fundamental computer vision problems: image segmentation. We propose a supervised hierarchical approach to object-independent image segmenta…
Disjunctive Normal Networks
Mehdi Sajjadi, Mojtaba Seyedhosseini, Tolga Tasdizen
Artificial neural networks are powerful pattern classifiers; however, they have been surpassed in accuracy by methods such as support vector machines and random forests that are al…
Scene Labeling with Contextual Hierarchical Models
Mojtaba Seyedhosseini, Tolga Tasdizen
Scene labeling is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual info…