README.md

metadata

language:
  - en
license: gpl-3.0
tags:
  - vision
  - image-segmentation
  - instance-segmentation
  - object-detection
  - optical-flow
  - depth
  - synthetic
  - sim-to-real
annotations_creators:
  - machine-generated
pretty_name: SMVB Dataset
size_categories:
  - 1K<n<10K
task_categories:
  - object-detection
  - image-segmentation
  - depth-estimation
  - video-classification
  - other
task_ids:
  - instance-segmentation
  - semantic-segmentation

Synthetic Multimodal Video Benchmark (SMVB)

A dataset consisting of synthetic images from distinct synthetic scenes, annotated with object/instance/semantic segmentation masks, depth data, surface normal information and optical for testing and benchmarking model performance for multi-task/multi-objective learning.

Supported Tasks and Leaderboards

The dataset supports tasks such as semantic segmentation, instance segmentation, object detection, image classification, depth, surface normal, and optical flow estimation, and video object segmentation.

Dataset Structure

Data Instances

Data Fields

Data Splits

Dataset Creation

Curation Rationale

Source Data

Citation Information

@INPROCEEDINGS{karoly2024synthetic,
  author={Károly, Artúr I. and Nádas, Imre and Galambos, Péter},
  booktitle={2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI)}, 
  title={Synthetic Multimodal Video Benchmark (SMVB): Utilizing Blender for rich dataset generation}, 
  year={2024},
  volume={},
  number={},
  pages={},
  doi={}}