Video Semantic Segmentation
322 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
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.
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.
RAP-SAM: Towards Real-Time All-Purpose Segment Anything
Segment Anything Model (SAM) is one remarkable model that can achieve generalized segmentation.
1st Place Solution for 5th LSVOS Challenge: Referring Video Object Segmentation
robertluo1/iccv2023_rvos_challenge
•
•
The recent transformer-based models have dominated the Referring Video Object Segmentation (RVOS) task due to the superior performance.
Tracking with Human-Intent Reasoning
The perception component then generates the tracking results based on the embeddings.
UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces
We evaluate our unified models on various benchmarks.
