We present Cutie a video object segmentation (VOS) network with object-level memory
reading which puts the object representation from memory back into the video object …

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 …

The reference-based object segmentation tasks, namely referring image segmentation
(RIS), referring video object segmentation (RVOS), and video object segmentation (VOS) …

Despite advancements in user-guided video segmentation, extracting complex objects
consistently for highly complex scenes is still a labor-intensive task, especially for …

Visual object tracking aims to localize the target object of each frame based on its initial
appearance in the first frame. Depending on the input modility tracking tasks can be divided …

Current state-of-the-art Video Object Segmentation (VOS) methods rely on dense per-object
mask annotations both during training and testing. This requires time-consuming and costly …

Open-vocabulary Video Instance Segmentation (OpenVIS) can simultaneously detect,
segment, and track arbitrary object categories in a video, without being constrained to …

Unsupervised video object segmentation (UVOS) aims at detecting the primary objects in a
given video sequence without any human interposing. Most existing methods rely on two …

Egocentric videos provide a first-person perspective of the wearer's activities involving
simultaneous interactions with multiple objects. In this work we propose the task of weakly …

With recent video object segmentation (VOS) benchmarks evolving to challenging scenarios
we revisit a simple but overlooked strategy: restricting the size of memory banks. This …