Example-driven Virtual Cinematography by Learning Camera Behaviors (SIGGRAPH 2020)
Source: https://history.siggraph.org/?p=78725
Structured fields
{
"checked_at": "2026-10-17T00:00:00.000Z",
"usefulness": "Direct precedent for 'learn camera behaviour from an example film clip and apply it to 3D animation': a cinematic feature space (angle, shot distance, composition, character arrangement) and a mixture-of-experts motion predictor. The research hypothesis the hub should test, not assume.",
"source_type": "paper",
"availability": "available",
"source_owner": "Jiang, Wang, Wang, Christie, Chen (ACM TOG 2020)",
"next_check_at": "2026-10-24T00:00:00.000Z",
"known_limitations": [
"Author project page jianghd1996.github.io returned 404 on 2026-10-17."
]
}Evidence claims
- [upstream_claim] Learns camera behavior from an example film clip and applies it to a 3D animation via a low-dimensional cinematic feature space and a cascaded model with Mixture-of-Experts gating. · locator: abstract source
- [sourced_fact] DOI 10.1145/3386569.3392427; SIGGRAPH 2020 Technical Papers, Cinematography session. · locator: record metadata source
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | prohibited | prohibited | prohibited | unknown | History archive states all rights reserved for featured text and images; the paper itself is ACM-published (rights not read). |