Zero Shot Segmentation

5 papers with code • 0 benchmarks • 0 datasets

This task has no description! Would you like to contribute one?

Most implemented papers

Context-aware Feature Generation for Zero-shot Semantic Segmentation

bcmi/CaGNet-Zero-Shot-Semantic-Segmentation 16 Aug 2020

In this paper, we propose a novel context-aware feature generation method for zero-shot segmentation named CaGNet.

Unsupervised Deep Learning for Bayesian Brain MRI Segmentation

voxelmorph/voxelmorph 25 Apr 2019

To develop a deep learning-based segmentation model for a new image dataset (e. g., of different contrast), one usually needs to create a new labeled training dataset, which can be prohibitively expensive, or rely on suboptimal ad hoc adaptation or augmentation approaches.

The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos

rt219/the-emergence-of-objectness NeurIPS 2021

Our model starts with two separate pathways: an appearance pathway that outputs feature-based region segmentation for a single image, and a motion pathway that outputs motion features for a pair of images.

Image Segmentation Using Text and Image Prompts

timojl/clipseg CVPR 2022

After training on an extended version of the PhraseCut dataset, our system generates a binary segmentation map for an image based on a free-text prompt or on an additional image expressing the query.

Language-driven Semantic Segmentation

isl-org/lang-seg ICLR 2022

We present LSeg, a novel model for language-driven semantic image segmentation.

Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs

kakaobrain/tcl 1 Dec 2022

Existing open-world segmentation methods have shown impressive advances by employing contrastive learning (CL) to learn diverse visual concepts and adapting the learned image-level understanding to the segmentation task.