Video Semantic Segmentation
325 papers with code • 5 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Video Semantic Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Video Semantic Segmentation models and implementations
Cityscapes
CamVid
SegTrack-v2
VSPW
MOSE
ODMS
LaRS
Latest papers
Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation
We hypothesize that the latent representation learned from a pretrained generative T2V model encapsulates rich semantics and coherent temporal correspondences, thereby naturally facilitating video understanding.
Video Object Segmentation with Dynamic Query Modulation
zht8506/qmvos
•
•
Storing intermediate frame segmentations as memory for long-range context modeling, spatial-temporal memory-based methods have recently showcased impressive results in semi-supervised video object segmentation (SVOS).
VideoMAC: Video Masked Autoencoders Meet ConvNets
nust-machine-intelligence-laboratory/videomac
•
•
In this paper, we propose a new approach termed as \textbf{VideoMAC}, which combines video masked autoencoders with resource-friendly ConvNets.
UniVS: Unified and Universal Video Segmentation with Prompts as Queries
minghanli/univs
•
•
Despite the recent advances in unified image segmentation (IS), developing a unified video segmentation (VS) model remains a challenge.
PolypNextLSTM: A lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM
Our primary novelty lies in PolypNextLSTM, which stands out as the leanest in parameters and the fastest model, surpassing the performance of five state-of-the-art image and video-based deep learning models.
Lester: rotoscope animation through video object segmentation and tracking
This article introduces Lester, a novel method to automatically synthetise retro-style 2D animations from videos.
We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline
simarkareer/unifiedvideoda
•
•
While the vast majority of prior work has studied this as a frame-level Image-DAS problem, a few Video-DAS works have sought to additionally leverage the temporal signal present in adjacent frames.
Vanishing-Point-Guided Video Semantic Segmentation of Driving Scenes
The estimation of implicit cross-frame correspondences and the high computational cost have long been major challenges in video semantic segmentation (VSS) for driving scenes.
Vivim: a Video Vision Mamba for Medical Video Object Segmentation
Traditional convolutional neural networks have a limited receptive field while transformer-based networks are mediocre in constructing long-term dependency from the perspective of computational complexity.
OMG-Seg: Is One Model Good Enough For All Segmentation?
lxtgh/omg-seg
•
•
In this work, we address various segmentation tasks, each traditionally tackled by distinct or partially unified models.
