281 citations · 381 across the 11 of their papers we have counts for
4 papers · 1 filter
CLIP as RNN: Segment Countless Visual Concepts without Training Endeavor
Shuyang Sun, Runjia Li, Philip Torr +2
Existing open-vocabulary image segmentation methods require a fine-tuning step on mask labels and/or image-text datasets. Mask labels are labor-intensive, which limits the number o…
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
Xiuye Gu, Yin Cui, Jonathan Huang +8
Observing the close relationship among panoptic, semantic and instance segmentation tasks, we propose to train a universal multi-dataset multi-task segmentation model: DaTaSeg.We u…
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models
James Urquhart Allingham, Jie Ren, Michael W Dusenberry +5
Contrastively trained text-image models have the remarkable ability to perform zero-shot classification, that is, classifying previously unseen images into categories that the mode…
Open-Vocabulary Temporal Action Detection with Off-the-Shelf Image-Text Features
Vivek Rathod, Bryan Seybold, Sudheendra Vijayanarasimhan +4
Detecting actions in untrimmed videos should not be limited to a small, closed set of classes. We present a simple, yet effective strategy for open-vocabulary temporal action detec…