Video Segmentation
105 papers with code • 1 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Video Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Datasets
BDD100K
SegTrack-v2
Dynamic Replica
PP-HumanSeg14K
PETRAW
EgoProceL
TikTok Dataset
ConferenceVideoSegmentationDataset
Infinity Spills Basic Dataset
Subtasks
Latest papers with no code
SimLVSeg: Simplifying Left Ventricular Segmentation in 2D+Time Echocardiograms with Self- and Weakly-Supervised Learning
From calculating biomarkers such as ejection fraction to the probability of a patient's heart failure, accurate segmentation of the heart structures allows doctors to assess the heart's condition and devise treatments with greater precision and accuracy.
SANPO: A Scene Understanding, Accessibility, Navigation, Pathfinding, Obstacle Avoidance Dataset
All synthetic sessions and a subset of real sessions have temporally consistent dense panoptic segmentation labels.
MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic Segmentation
Then, we propose a semantic mining module that takes the object masks to refine the pseudo labels in the target domain.
MEGA: Multimodal Alignment Aggregation and Distillation For Cinematic Video Segmentation
Previous research has studied the task of segmenting cinematic videos into scenes and into narrative acts.
Large-scale environment mapping and immersive human-robot interaction for agricultural mobile robot teleoperation
For control, a closed-loop system utilizing TCP for VR control and positioning of agricultural machinery was introduced.
Stochastic positional embeddings improve masked image modeling
Masked Image Modeling (MIM) is a promising self-supervised learning approach that enables learning from unlabeled images.
Automatic Interaction and Activity Recognition from Videos of Human Manual Demonstrations with Application to Anomaly Detection
This paper presents a new method to describe spatio-temporal relations between objects and hands, to recognize both interactions and activities within video demonstrations of manual tasks.
A Unified Multiscale Encoder-Decoder Transformer for Video Segmentation
In this paper, we present an end-to-end trainable unified multiscale encoder-decoder transformer that is focused on dense prediction tasks in video.
A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware design
Semantic image and video segmentation stand among the most important tasks in computer vision nowadays, since they provide a complete and meaningful representation of the environment by means of a dense classification of the pixels in a given scene.
Learning to Adapt to Online Streams with Distribution Shifts
Test-time adaptation (TTA) is a technique used to reduce distribution gaps between the training and testing sets by leveraging unlabeled test data during inference.
