Michael Black Questions the Role of Academic CV Research in the Era of Large Models
Michael J. Black, a veteran computer vision researcher at the Max Planck Institute who has attended ECCV since 1992, posted a long essay before ECCV 2026 questioning the role of academic CV research in the era of large models, drawing responses from peers including MIT professor Phillip Isola.
Confirmed
- Black's paper this year, VIGA, uses an agentic approach to convert images into 3D Blender scenes (a Vision-as-Inverse… idea). It was rejected on first submission and, after delayed publication, was already surpassed by stronger models.
- Black's central questions: with models growing ever more capable, what is the point of academic CV research? Is GPT-6 "Astra" a step change? How can researchers have impact in academia today?
- Phillip Isola responded that one direction is to do less "task solving" and more "understanding solutions": he argued a paper analyzing how Astra plus open-source models work could have greater value.
- In a follow-up, Black elaborated that academia's inability to evaluate top-tier models is a key problem requiring coordination among model companies, governments, and academic leaders.
Why it matters
- The discussion reflects the shock that rapidly iterating foundation models are delivering to traditional academic research: papers are obsolete on arrival, and academia's comparative advantage is shifting from building models to analysis and understanding—even evaluation itself is becoming a task academia cannot shoulder alone.
- Black and Isola represent two voices—the reflector and the path-giver—offering young researchers a framework for choosing research directions in the era of large models.
2026-09-09 ~ 2026-09-10 · 7 related posts
- Episode 1: Michael Black Questions the Role of Academic CV Research in the Era of Large Models(2026-09-09, 7 posts)
- Episode 2: Post-GPT-6 gloom at ECCV as researchers fear CV work being absorbed by foundation models(2026-09-17, 6 posts)
- Episode 3: VIGA thread: exhaust LLMs first; paper cycles lag behind models(2026-09-18, 2 posts)
- Episode 4: Scholars argue research should first stress-test existing LLMs(2026-09-18, 2 posts)
Primary sources
- CV veteran Michael Black: ECCV papers are two years stale — academia must rethink how it works — Michael_J_Black ·
- Michael Black on academia's role in the era of powerful large models — Michael_J_Black ·
- Phillip Isola: Study How Big Models Solve Tasks, Don't Race Them on New Benchmarks — phillip_isola ·
- [source] CV veteran Michael Black: ECCV papers are two years stale — academia must rethink how it works — Michael_J_Black · 2026-09-09
- ECCV veteran asks what academic CV research means in the age of frontier models — CharlotteHase · 2026-09-09
- MPI's Michael Black: Learning About VIGA at ECCV 2026 Means You're Late to the Party — Michael_J_Black · 2026-09-09
- [source] Phillip Isola: Study How Big Models Solve Tasks, Don't Race Them on New Benchmarks — phillip_isola · 2026-09-09
- Michael Black on academic CV research's role in the age of powerful large models — CSProfKGD · 2026-09-10
- [source] Michael Black on academia's role in the era of powerful large models — Michael_J_Black · 2026-09-10
1 near-duplicate retellings: prof_kamilov