This work presents AnyDoor a diffusion-based image generator with the power to teleport
target objects to new scenes at user-specified locations with desired shapes. Instead of …

We introduce a novel sequential modeling approach which enables learning a Large Vision
Model (LVM) without making use of any linguistic data. To do this we define a common …

Training data for video segmentation are expensive to annotate. This impedes extensions of
end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary …

Video object segmentation (VOS) aims at segmenting a particular object throughout the
entire video clip sequence. The state-of-the-art VOS methods have achieved excellent …

In this work we address various segmentation tasks each traditionally tackled by distinct or
partially unified models. We propose OMG-Seg One Model that is Good enough to efficiently …

Visual segmentation seeks to partition images, video frames, or point clouds into multiple
segments or groups. This technique has numerous real-world applications, such as …

We present Segment Anything Model 2 (SAM 2), a foundation model towards solving
promptable visual segmentation in images and videos. We build a data engine, which …

This paper presents Video K-Net, a simple, strong, and unified framework for fully end-to-
end video panoptic segmentation. The method is built upon K-Net, a method that unifies …

Video segmentation aims to segment and track every pixel in diverse scenarios accurately.
In this paper, we present Tube-Link, a versatile framework that addresses multiple core tasks …

Recently, pre-trained vision-language models have been increasingly used to tackle the
challenging zero-shot segmentation task. Typical solutions follow the paradigm of first …