The research advances concerning the typical architectures of convolutional neural
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …

Recently integrating video foundation models and large language models to build a video
understanding system can overcome the limitations of specific pre-defined vision tasks. Yet …

We present XMem, a video object segmentation architecture for long videos with unified
feature memory stores inspired by the Atkinson-Shiffrin memory model. Prior work on video …

Transformer trackers have achieved impressive advancements recently, where the attention
mechanism plays an important role. However, the independent correlation computation in …

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 top-leading solutions for video object segmentation (VOS) typically follow a
matching-based regime: for each query frame, the segmentation mask is inferred according …

Optical flow is an easily conceived and precious cue for advancing unsupervised video
object segmentation (UVOS). Most of the previous methods directly extract and fuse the …

Abstract Space-time memory (STM) based video object segmentation (VOS) networks
usually keep increasing memory bank every several frames, which shows excellent …

Recently, memory-based approaches show promising results on semi-supervised video
object segmentation. These methods predict object masks frame-by-frame with the help of …

The current popular methods for video object segmentation (VOS) implement feature
matching through several hand-crafted modules that separately perform feature extraction …