Latest News
The 8th LSVOS Challenge will be held in conjunction with ECCV 2026. Stay tuned for updates!
Announcement
[IMPORTANT] Team Information Requirement for Submission – Update from Previous Challenge
Starting from this year’s challenge, all submissions must include a valid team information file
(team.json) in the submission package. This will help us contact you more efficiently.
Submitting team information is mandatory. The details in team.json will
be treated
as your final team information. Please ensure the provided email address is valid and reachable,
as it will be our only means of contact. Submissions with missing, false, or empty team information,
or with invalid/unreachable emails, may be considered invalid.
To avoid duplicate accounts, each research center / institute / lab may only register one team. If colleagues from the same affiliation are also participating, please merge into a single team before submission. If we detect multiple teams from the same affiliation, we reserve the right to disqualify all related teams.
Example team.json (place in the root submission folder, at the same level as the video folders):
{
"By submitting the test results, I agree with the challenge terms and policies.": true,
"team_name": "Put_your_team_name_here",
"members": [
{"name": "Member A", "affiliation": "University A"},
{"name": "Member B", "affiliation": "Company A"},
{"name": "Member C", "affiliation": "Institute A"}
],
"email": "your_email@example.edu"
}
Introduction
The 8th LSVOS challenge will be held in conjunction with ECCV 2026 in Malmö, Sweden. This year, we will continue the same setup as last year and still have two tracks: VOS and RVOS. In the Video Object Segmentation (VOS) track, we will utilize LVOS and MOSE. to study the VOS under more challenging complex environments. LVOS is designed for long-term videos, dealing with complex object motion and long-term reappearance, while MOSE focuses on complex scenes, covering aspects such as object disappearance and reappearance, inconspicuous small objects, heavy occlusions, and crowded environments. For the Referring Video Object Segmentation (RVOS) track, we will continue to use MeViS. MeViS focuses on the identification of the target object in a video based on motion-related descriptions rather than static attributes. This innovative approach subverts the foundational design principles of existing RVOS methods, compelling researchers to engage in a more in - depth exploration and reevaluation of motion modeling. In addition, we will hold a series of talks by the leading experts in video understating and embodied intelligence. In this year, the following topics will be covered:
- Semantic/panoptic segmentation for images/videos
- Video Object Segmentation in Complex Scenes
- Long-term Video Object Segmentation
- Referring Video Object Segmentation
- Video Segmentation with Motion Expressions
- Vision and Language
- Cognitive Models of Object Perception
- Real-world Understanding and embodied intelligence
Challenge Timeline
| Event | Date |
|---|---|
| Challenge Release | TBD |
| Validation Server Online | TBD |
| Test Server Online | TBD |
| Submission Deadline | TBD |
| Notification of Results | TBD |
Call for Paper
[Update] LSVOS 2026 paper submission details will be announced soon. Stay tuned!
We invite authors to submit unpublished papers (8-page ECCV format) to our workshop, to be presented at a poster session upon acceptance. All submissions will go through a double-blind review process. Submission portal link will be announced later.
Accepted papers will be published in the official ECCV Workshops proceedings and the Computer Vision Foundation (CVF) Open Access archive.
Paper Submission Timeline
| Event | Date |
|---|---|
| Submission portal open | TBD |
| Regular paper submission deadline | TBD |
| Supplemental material deadline | TBD |
| Notification of paper acceptance | TBD |
| Camera ready deadline | TBD |
Challenge Tracks & Submission
The 8th LSVOS challenge includes three tracks: Complex VOS (MOSEv2), Classic VOS and RVOS.
Below are the links and task descriptions for the three tracks:
Track 1: Complex Video Object Segmentation (MOSEv2)
MOSEv2 focuses on VOS in complex scenes with frequent object disappearance and reappearance, severe occlusions, smaller targets, and new challenges including adverse weather, low light, multi-shot sequences, camouflage, non-physical targets, and knowledge-dependent scenarios. Submission server: TBD
Track 2: Video Object Segmentation (Classic VOS)
The video object segmentation task aims to segmenting a particular object instance throughout the entire video sequence given only the object mask of the first frame. The dataset is a mixture of MOSEv1 and LVOS datasets. Submission server: TBD
Track 3: Referring Video Object Segmentation (RVOS)
Referring video object segmentation aims to segment an object in video with language expressions. Submission server: TBD
Leaderboard
TBD
Workshop Schedule
TBD
Speakers
TBD
Organizers
Lingyi Hong
Fudan University
Henghui Ding
Fudan University
Chang Liu
SUFE
Ning Xu
Apple Inc.
Linjie Yang
ByteDance Inc.
Yuchen Fan
Meta Reality LabsContact
Feel free to contact us:
henghui.ding@gmail.com
honglyhly@gmail.com
liuc0058@e.ntu.edu.sg