Skill UI

A comprehensive guide for authors preparing their accepted ECCV papers for multiple publication venues, including Springer LNCS, ECVA open-access portals, and arXiv. It details critical steps such as managing page budgets, ensuring metadata accuracy, fulfilling rebuttal promises, and adhering to strict publication deadlines.

A comprehensive guide for designing and auditing high-stakes computer vision experiments for top-tier conferences. It covers critical areas like 'matched-substrate fairness,' 'six-month-staleness testing,' and rigorous ablation studies, ensuring that claims are robust, reproducible, and withstand intense peer review scrutiny.

A comprehensive guide for positioning novel research in elite computer vision and AI conferences (e.g., ECCV). It details how to structure the related work section by tracing academic lineage, handling concurrent work, verifying citation hygiene across venues (CVPR, ICCV, ECCV), and transforming simple bibliographies into strong, argumentative prose. Essential for improving novelty visibility.

A comprehensive guide for authors submitting computer vision papers (e.g., to ECCV). It outlines best practices for ensuring the full reproducibility of AI research, covering everything from detailed training recipes and hyperparameter logging to pinning foundation model dependencies and reporting variance honesty. Essential for academic publication integrity.

A detailed guide for modeling the complete academic peer-review lifecycle, specifically tailored to the ECCV conference structure. It covers the timeline from submission through rebuttal and AC discussion to final decision, detailing critical points such as co-author enforcement regimes, LLM policy adherence, panel reviewer composition, and strategic points influencing the final outcome. Essential for researchers targeting top-tier vision conferences.

A detailed auditing guide for submitting to major academic conferences, such as ECCV. It covers critical aspects including multi-stage submission deadlines (CET timezone), strict LNCS formatting rules (14 pages single-column), policy adherence (dual-submission, embargo rules), and pre-upload checks to mitigate rejection risks. Essential for researchers managing academic publishing workflows.

This guide provides comprehensive instructions for preparing and submitting supplementary material for computer vision conferences like ECCV. It details how the supplement should support the main paper's claims without adding new results, covering topics such as qualitative result visualization, detailed ablation studies, code archive scrubbing, and ensuring full anonymity across all uploaded assets.

A comprehensive guide for computer vision researchers to determine if their project is a good fit for ECCV, considering scope, technical durability, and academic timing. It weighs the project's contribution against the specific requirements of ECCV versus competing top-tier venues like CVPR and ICCV, ensuring strategic submission planning.

This guide outlines the complete project management workflow for major computer vision conferences like ECCV, CVPR, and ICCV. It covers the entire academic cycle, from initial registration and submission through peer review, acceptance, camera-readiness, and post-conference retargeting strategies. Useful for research teams planning multiple submissions across even and odd years.

A comprehensive guide for drafting and compressing academic manuscripts, focusing on strict formatting constraints (e.g., LNCS single-column, 14-page limit) typical of major conferences like ECCV. Learn how to structure your paper, optimize the first page for non-specialists, and phrase claims to withstand rigorous peer review and rebuttal.

A comprehensive guide for structuring, auditing, and writing mathematically rigorous proofs for advanced academic papers, particularly in econometrics and statistics. It covers everything from defining assumptions and stating self-contained theorems to applying advanced proof techniques (e.g., fixed-point theorems, CLT). Use this when your central result requires impeccable rigor and completeness for top-tier publication.

This comprehensive guide assists authors in strategically positioning their computer vision manuscripts for the European Conference on Computer Vision (ECCV). It covers conference fit assessment, manuscript re-framing, required evidence (e.g., ablations, baselines, failure modes), and structural advice to ensure the work aligns with ECCV's scope and current review policies. Use this tool for venue selection and submission preparation.