Use when targeting European Conference on Computer Vision (ECCV) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for computer vision flagship.
SkillScore78Maintained
Automatic
◆Research pack
Last verified 9/2/2026
What it changes
Passed 18 of 23 test cases with the skill, and 10 of 23 without it.
Without skill43%
With skill78%
Checks it passed that the model alone missed
Rates [Fit] as Low.
Rates [Fit] as High.
Names eccv.ecva.net as the official anchor domain.
and 11 more in the full report
9 fixed9 passed either way4 still failing1 broke
Pass-rate lift
+35 pp
Tokens
+64%
Agent turns
0%
Response time
-22%
Model gemini-3.6-flashMeasured 9/2/2026v118 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 9
Prompt
We have developed a lightweight vision-language framework for fine-grained action recognition in long untrimmed videos, accompanied by a new synthetic evaluation dataset. We are considering submitting to ECCV. Could you run a venue strategy assessment on this paper concept? Please output your evaluation using these exact output headers:
[Fit] (High/Medium/Low plus single-sentence justification)
[Target] (Target conference name)
[Contribution type] (Primary category of contribution)
[Main evidence gap] (Single most critical missing proof, test, or baseline)
[Official items to re-check] (Key venue rules and administrative requirements to double-check)
[Top rejection risk] (Main venue-specific risk factor)
[Re-route suggestion] (Alternative target venue if not optimal for ECCV)
What was checked, without and with the skill
Checked
Without skill
With skill
Includes the exact line [Target] European Conference on Computer Vision (ECCV).
Missed
Passed
Selects a single category from the defined taxonomy list for contribution type.
Missed
Passed
Renders header lines using single bracketed key-value lines instead of markdown subheadings.
Passed
Passed
case-02 · gemini-3.6-flash · 9/2/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md106 linessingle file
European Conference on Computer Vision (ECCV)
Conference positioning
European Conference on Computer Vision (ECCV) is a top computer-science conference venue for European computer vision across learning, geometry, perception, generation, and applications. It rewards a strong CV paper suited to a broad computer-vision audience and current ECCV review policies. Treat this skill as a fit / venue-selection / re-framing tool for conference submission strategy, not as a substitute for the current year's CFP, author kit, ethics policy, or submission portal.
Because CS conferences change deadlines, templates, page limits, review workflow, artifact rules, AI-use policy, and rebuttal formats every cycle, always verify the live official instructions before making a submission-ready recommendation. Start from the official source anchor recorded for this venue in ../../resources/conference-roster.md and ../../resources/official-source-map.md.
When to trigger
The author names ECCV / European Conference on Computer Vision as the target venue.
A manuscript in European computer vision across learning needs a conference-fit read before being formatted or submitted.
The paper must be re-framed from journal style or arXiv style into a selective CS conference narrative.
The author needs an evidence-gap, anonymity, artifact, rebuttal, or re-routing diagnosis for this venue.
Scope & topic fit
Core fit: European computer vision across learning, geometry, perception, generation, and applications.
Best submissions make a precise contribution type visible: algorithm, theorem, system, dataset, benchmark, empirical finding, design artifact, tool, or socio-technical analysis.
The paper should explain why the result matters to ECCV's reviewers, not just why it is interesting to the authors' lab or product context.
Position related work against the most recent conference-cycle papers in this venue and its closest siblings; stale comparisons are a common early-review weakness.
If the contribution is interdisciplinary, state which part is CS research and which part is domain evidence.
Venue-specific calibration
Reviewer lens: Read reviewers as CV specialists. Strong ablations, dataset protocols, qualitative failures, and current vision baselines are mandatory.
Contribution hook to foreground: the venue-specific contribution bar.
Scope vocabulary to use naturally in the abstract and introduction: European computer vision across learning, geometry, perception, generation, and applications.
Official anchor domain: eccv.ecva.net. Quote annual rules only after opening that source and the current-year CFP/author kit.
Close-neighbor routing guardrail
Route to ECCV when the paper is a computer-vision contribution and the current cycle/community
fit makes the European vision flagship the right target.
Do not distinguish ECCV from ICCV/CVPR by prestige alone. Match the live cycle, topic area,
benchmark culture, and reviewer expectations; use WACV/ACCV/BMVC for different scope or
timing.
What distinguishes this venue from its closest siblings
Use when targeting IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for computer vision flagship.
Use when targeting European Symposium on Research in Computer Security (ESORICS) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for security.