Skill UI

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.

This guide outlines the rigorous, multi-stage process for submitting camera-ready versions for a top-tier academic conference like FOCS. It details the critical difference between the official IEEE proceedings and the public arXiv/ECCC full version. Key steps include de-anonymization, maintaining source consistency across both documents, updating author details, and preparing for conference talks and awards eligibility.

A comprehensive guide for structuring the "Related Work" section for top-tier computer vision conferences (ICCV, CVPR, ECCV). It covers best practices for citing intervening-cycle literature, managing concurrent preprints, ensuring double-blind anonymity, and correctly attributing source venues to maximize novelty perception and score highly with reviewers.

A comprehensive guide for researchers deciding the optimal venue for a computer vision project. It analyzes the biennial nature of top conferences like ICCV, evaluating project readiness, timing maturity, and comparing the unique requirements of ICCV, CVPR, and ECCV to maximize acceptance chances.

This guide provides a structured framework for responding to reviewers and editors regarding a meta-analysis or systematic synthesis. Because such revisions often involve expanding the search, changing eligibility criteria, or adding complex bias diagnostics, the response must maintain impeccable internal statistical consistency across all tables, figures, and estimates. It ensures all methodological changes are clearly propagated and justified.

This guide helps researchers determine the optimal venue for their Computer Vision paper, specifically addressing the unique identity of WACV (Applications-first) versus major conferences like CVPR, ICCV, and ECCV. It guides authors on whether their contribution is driven by real-world applications/constraints or by advancing core algorithms, and how to choose between the Applications or Algorithms track within WACV.