IEEE TPAMI 'Under Review': What Each Status Means and When to Expect a Decision

Before the paper reaches external reviewers, an IEEE TPAMI Associate Editor evaluates whether the methodology significance, comparison to state-of-the-art rigor, and standardized benchmark coverage warrant IEEE TPAMI's editorial slots. About 40 to 50 percent of submissions are desk-rejected at this stage within 1 to 3 weeks.

A desk rejection most often means the editor concluded that the work is pure application without methodology contribution, lacks comprehensive comparison to state-of-the-art, has insufficient standardized benchmark coverage, or would fit better at a sister IEEE journal (IEEE Transactions on Image Processing for image processing, IEEE Transactions on Neural Networks and Learning Systems for neural network theory, IEEE Computer Vision conferences for CVPR/ICCV/ECCV).

The IEEE TPAMI editorial office confirms files are complete: manuscript with figures embedded, Supporting Information with benchmark results on standardized datasets, IEEE template formatting, cover letter directed to the editor naming methodology contribution and benchmark coverage, conflict-of-interest declarations, ethics-statement documentation, and data-availability statement (including code and pretrained model release where applicable).

The Associate Editor reads the paper and evaluates pattern-analysis-and-machine-intelligence methodology significance, comparison to state-of-the-art, standardized benchmark coverage, and IEEE TPAMI subspecialty routing.

In parallel with the Associate Editor's primary read, ambiguous-fit papers are discussed across the IEEE Computer Society editorial team where peer Associate Editors weigh in on whether the paper would fit better at IEEE TPAMI or at sister IEEE journals. This editorial consultation runs alongside the desk-screen and adds 3 to 5 days to the timeline that is invisible to the author in the portal.

IEEE TPAMI Associate Editors invite 3 reviewers per IEEE Computer Society advocacy, with reviewer recruitment typically taking 7 to 14 days. The 3-reviewer model is harder to recruit than 2-reviewer norms, and reviewers with topic-matched pattern-analysis-and-machine-intelligence subspecialty expertise are scarce.

Once 3 reviewers agree to review, the typical IEEE TPAMI peer-review cycle lasts 4 to 6 weeks per reviewer per IEEE guidance. Reviewers are asked to evaluate methodology significance, comparison to state-of-the-art rigor, benchmark coverage adequacy, and reproducibility. Reviewer reports for IEEE TPAMI tend to be thorough; 2000 to 4000 word reports are typical given the 3-reviewer model.

After 3 reports return, the Associate Editor is given 1 to 2 weeks to analyze the reviewer's comments and make a recommendation. Total submission-to-acceptance commonly runs 6 to 14 months for successful papers, including revision rounds.

• Rejection within 1 to 7 days: Administrative issue or immediate scope mismatch.

• Rejection within 7 to 21 days: Associate Editor desk rejection per the 40 to 50 percent figure.

• Still Under Review after 3 weeks: Strong signal. Paper passed the Associate Editor filter.

• Still Under Review after 16 weeks: Reviewer-recruitment or 3-reviewer-model delay. A polite inquiry via the ScholarOne portal is appropriate.

• Status changes to "Decision Pending": 3 reports are in; expect a decision within 1 to 2 weeks after Associate Editor analysis.

This is the most common anxiety we hear from IEEE TPAMI authors during the active editorial window. The honest answer: no, 10 weeks at Under Review puts you in the normal middle of IEEE TPAMI's 8 to 16 week full peer-review distribution for the 3-reviewer model. Reports may still be arriving with the Associate Editor preparing for the 1 to 2 week analysis-and-recommendation window.

Most reviewer-driven delays come from the 3-reviewer model recruitment difficulty (the IEEE Computer Society strongly advocates 3 reviews) rather than slow reviews. If the portal still says Under Review at the 16-week mark, the most likely explanation is that one or more of the 3 assigned reviewers asked for an extension and the Associate Editor granted it. This is normal practice at IEEE TPAMI.

What you should NOT do during the 10-to-16-week window is email the editorial office. IEEE TPAMI Associate Editors are working academic computer vision researchers managing 60+ active papers per year; an inquiry at 10 weeks adds friction without accelerating the timeline.

If your IEEE TPAMI paper is rejected after review, the natural cascade depends on what the reviewers and Associate Editor cited:

IEEE Transactions on Image Processing is the natural IEEE Signal Processing Society cascade for image processing methodology papers.

IEEE Transactions on Neural Networks and Learning Systems is the IEEE Computational Intelligence Society cascade for neural network theory.

IEEE Transactions on Multimedia is the IEEE cascade for multimedia analysis.

IEEE Computer Vision conferences (CVPR, ICCV, ECCV) are the natural cascades for conference-format papers; CVPR uses a separate openreview.net submission system.

International Journal of Computer Vision (IJCV) is the external Springer cascade for top-tier computer vision methodology. IJCV uses Editorial Manager at Editorial Manager submission portal; editorial contact ijcv at Springer Nature journal page.

JMLR (Journal of Machine Learning Research) is the external machine learning cascade; JMLR uses jmlr.org submission system.

IEEE asks reviewers at TPAMI to evaluate four things specifically. The table below maps each to actionable preparation.

Across Manusights submission reviews for IEEE TPAMI-targeted papers, and in our review of 50+ nearby machine-intelligence manuscripts, Manusights review data shows three named patterns generate the most consistent reviewer concerns and the most common reasons papers miss the IEEE TPAMI editorial bar or fail the Associate Editor screen. The problem is usually not a missing benchmark alone.

It is a mismatch between what the paper claims in the abstract and what the methods, experiments, ablations, and reproducibility package actually prove. TPAMI reviewers read for durable pattern-analysis or machine-intelligence methodology, not only for a strong result on one application dataset.

Pure-application framing flagged at IEEE TPAMI Associate Editor screen. When the title, abstract, and introduction present an application result without a clear methodology contribution, IEEE TPAMI desk rejection within 1 to 3 weeks is common. The strongest manuscripts name the technical advance explicitly, explain why existing methods cannot solve the same problem, and show where the algorithmic contribution sits in the pipeline. If the methods section reads like an engineering integration rather than a reusable method, the paper is usually a better fit for a specialty application venue.

Check whether your IEEE TPAMI method claim is visible →

Benchmark coverage gaps surface as TPAMI reviewer concerns. When the experiments section does not include standardized benchmark results on widely used datasets such as ImageNet, COCO, ADE20K, KITTI, Cityscapes, or the relevant field-standard alternative, reviewers consistently request more evidence. The gap is not just "add a dataset." Reviewers look for recent baselines, fair hyperparameter treatment, ablations that isolate the proposed component, statistical stability across seeds, and error analysis that explains where the method fails.

A custom dataset alone rarely carries a TPAMI submission unless the paper also proves methodological generality.

Check if your IEEE TPAMI benchmark package is reviewer-ready →

IEEE family cascade offers from Associate Editor. When the Associate Editor concludes the work is rigorous but the methodology priority bar of IEEE TPAMI is not met, transfer offers to IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, or IEEE Transactions on Multimedia are common.

The manuscript component that determines the cascade is usually the contribution statement: image-processing methodology points to TIP, neural-network theory points to TNNLS, and media-analysis framing points to TMM. Before submission, the most useful fix is to make the abstract, contribution list, benchmark table, code-availability statement, and limitations section speak to the TPAMI methodology bar rather than to a narrow application win.

Check your IEEE TPAMI cascade response plan →

This guide tells you what IEEE TPAMI editors look for while the manuscript is being routed or reviewed. The review tells you whether your paper passes that methodology-and-benchmark check before the decision arrives. Manusights has reviewed 50+ papers targeting IEEE TPAMI and nearby machine-intelligence venues, offers a 60-day money-back guarantee for eligible review orders, and we do not train AI on private author manuscripts.

Source limitation: this guidance combines official guidance, public status/timing signals, and anonymized Manusights pre-submission review patterns; it does not use private IEEE editorial records. Compared with official guidance, the useful reader-facing value is translating the status into benchmark, ablation, and reproducibility checks authors can act on while waiting.

This page was created from IEEE's public TPAMI information for authors at ieeexplore.ieee.org, IEEE Computer Society editorial documentation (3-reviewer advocacy, 4 to 6 week reviewer target, 1 to 2 week Associate Editor analysis-and-recommendation window, double-blind peer review, methodology-not-applications focus, standardized benchmark coverage expectation), and Manusights pre-submission review experience with IEEE TPAMI-targeted manuscripts.

For the IEEE pattern-analysis-and-machine-intelligence landscape beyond IEEE TPAMI, see IEEE Transactions on Image Processing (image processing methodology), IEEE Transactions on Neural Networks and Learning Systems (neural network theory), IEEE Transactions on Multimedia (multimedia analysis), IEEE Computer Vision conferences (CVPR, ICCV, ECCV), and external computer vision alternatives (International Journal of Computer Vision, JMLR, NeurIPS, ICML).

The choice across these titles depends on whether the central contribution is top-tier pattern-analysis-machine-intelligence journal methodology (IEEE TPAMI), image processing methodology (IEEE TIP), neural network theory (IEEE TNNLS), multimedia analysis (IEEE TMM), conference vision (CVPR/ICCV/ECCV), top journal computer vision (IJCV), machine learning theory (JMLR), or top ML conferences (NeurIPS, ICML).

For stronger cluster routing, compare this page with the IEEE TPAMI submission guide, International Journal of Computer Vision under review, IEEE Transactions on Medical Imaging under review, and Astrophysical Journal under review for adjacent computational-review timing patterns.

Reviewers at IEEE TPAMI typically draw from 3 pattern-analysis-and-machine-intelligence subspecialty experts under a double-blind 3-reviewer model. Editors screen and triage manuscripts before any external reviewer sees them, and preparing a response template that addresses methodology significance, benchmark coverage, and reproducibility accelerates revision rounds substantially.

For a pre-upload check of your manuscript against the IEEE TPAMI methodology-plus-benchmark bar before submission, our IEEE TPAMI pre-submission diagnostic flags the methodology framing and benchmark coverage weaknesses most likely to surface in reviewer reports.