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
Most implemented papers
Efficient Hierarchical Graph-Based Segmentation of RGBD Videos
We present an efficient and scalable algorithm for segmenting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based approach.
Actor and Action Video Segmentation from a Sentence
This paper strives for pixel-level segmentation of actors and their actions in video content.
Few-Shot Segmentation Propagation with Guided Networks
Learning-based methods for visual segmentation have made progress on particular types of segmentation tasks, but are limited by the necessary supervision, the narrow definitions of fixed tasks, and the lack of control during inference for correcting errors.
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video
We present Accel, a novel semantic video segmentation system that achieves high accuracy at low inference cost by combining the predictions of two network branches: (1) a reference branch that extracts high-detail features on a reference keyframe, and warps these features forward using frame-to-frame optical flow estimates, and (2) an update branch that computes features of adjustable quality on the current frame, performing a temporal update at each video frame.
Adaptive Temporal Encoding Network for Video Instance-level Human Parsing
HCPLab-SYSU/ATEN
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Beyond the existing single-person and multiple-person human parsing tasks in static images, this paper makes the first attempt to investigate a more realistic video instance-level human parsing that simultaneously segments out each person instance and parses each instance into more fine-grained parts (e. g., head, leg, dress).
Meta Learning Deep Visual Words for Fast Video Object Segmentation
We address this problem by considering the task of video object segmentation.
Spatiotemporal CNN for Video Object Segmentation
longyin880815/STCNN
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CVPR 2019
Specifically, the temporal coherence branch pretrained in an adversarial fashion from unlabeled video data, is designed to capture the dynamic appearance and motion cues of video sequences to guide object segmentation.
Self-supervised Learning for Video Correspondence Flow
zlai0/CorrFlow
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Fourth, in order to shed light on the potential of self-supervised learning on the task of video correspondence flow, we probe the upper bound by training on additional data, \ie more diverse videos, further demonstrating significant improvements on video segmentation.
Semantic Segmentation of Video Sequences with Convolutional LSTMs
Andreas-Pfeuffer/LSTM-ICNet
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The disadvantage of this is that temporal image information is not considered, which improves the performance of the segmentation approach.
Learning Unsupervised Video Object Segmentation Through Visual Attention
This paper conducts a systematic study on the role of visual attention in Unsupervised Video Object Segmentation (UVOS) tasks.
