# pengsida/learning_research

本人的科研经验

Repository: https://github.com/pengsida/learning_research
Canonical: https://ross.abutalabs.com/products/learning_research
License Family: other
Last push: 2026-06-06T10:00:56+00:00

## Health v2 (maintenance only)
Score: 68/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 86, release rhythm 35, longevity 86
- inputs: {"age_days": 1213, "days_push": 88, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 13855, forks 680 (observed 2026-08-28T04:11:04.965189+00:00)

## What it is
An open-source collection of research experience and advice for graduate and undergraduate students, written by a 3D vision researcher. It covers finding research problems, generating ideas, running experiments, paper writing, rebuttals, and presentations, with links to slides and course videos.

## Use cases
- how to become a top PhD student
- how to get started in 3D vision research
- how to write academic papers
- how to prepare rebuttals for paper reviews
- how to give academic presentations
- how to choose research topics and build field vision

## When to choose
- you are a new graduate student learning how to do research
- you want advice on paper writing, rebuttals, and presentations
- you are interested in 3D vision or graphics research careers

## When to avoid
- you need technical code or tools rather than research guidance
- you need advice outside the author's academic context and field

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: education, tutorials, computer-vision
- platform: -
- tags: research-advice, phd, academic-writing, 3d-vision, chinese-language, awesome-lists, web-server

## Member repositories
- pengsida/learning_research (main) score 68

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:04.965189+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:12:59.564839+00:00, confidence not recorded.
  - readme: https://github.com/pengsida/learning_research (fetched 2026-08-28T04:11:04.965189+00:00, sha 886059c8e39f)
- Data as of 2026-08-30T08:39:29.467469+00:00.