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 …

Current referring video object segmentation (R-VOS) techniques extract conditional kernels
from encoded (low-resolution) vision-language features to segment the decoded high …

We propose Hi4D, a method and dataset for the auto analysis of physically close human-
human interaction under prolonged contact. Robustly disentangling several in-contact …

Memory-based methods in semi-supervised video object segmentation task achieve
competitive performance by performing dense matching between query and memory frames …

This paper tackles the problem of semi-supervised video object segmentation on resource-
constrained devices, such as mobile phones. We formulate this problem as a distillation …

This paper studies referring video object segmentation (RVOS) by boosting video-level
visual-linguistic alignment. Recent approaches model the RVOS task as a sequence …

This paper studies open-vocabulary segmentation (OVS) through calibrating in-vocabulary
and domain-biased embedding space with generalized contextual prior of CLIP. As the core …

This paper aims to achieve universal segmentation of arbitrary semantic level. Despite
significant progress in recent years specialist segmentation approaches are limited to …

Change detection is a prominent research direction in the field of remote sensing image
processing. However, most current change detection methods focus solely on detecting …

Detecting mirrors from static images has received significant research interest recently.
However, detecting mirrors over dynamic scenes is still under-explored due to the lack of a …