Home › Code › compute_scale_and_shift

compute_scale_and_shift

Syntologyentry name in harvested coderead from the graph 2026-09-24

compute_scale_and_shift appears in the code Syntology harvested for 8 papers, as 5 distinct code bodies found in 8 places (a place is one code body under one paper). At least one of them ran in 6 of the papers; 1 of the code bodies carries a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named compute_scale_and_shift do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 3 of the 5 distinct code bodies named compute_scale_and_shift; 2 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
3ran
2unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 2 of the 8 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

8 papers shown of 8, newest first; 8 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost 9 May 2024 ethanygao/Aux-NAS/loss/losses.py 25ba9b5031480973 ran no licence file found · pointer only
What Matters When Repurposing Diffusion Models for General Dense Perception Tasks? 10 Mar 2024 aim-uofa/genpercept/genpercept/losses/geometry_losses.py 42fe451082384fe7 ran fingerprinted BSD-2-Clause (permissive)
ZeroShape: Regression-based Zero-shot Shape Reconstruction 21 Dec 2023 zxhuang1698/ZeroShape/model/depth/midas_loss.py 2ca5802395ca8c2c ran no licence file found · pointer only
ObjectSDF++: Improved Object-Compositional Neural Implicit Surfaces 15 Aug 2023 qianyiwu/objectsdf_plus/code/model/loss.py 25ba9b5031480973 ran MIT (permissive)
Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model 9 Jun 2023 yc015/scene-representation-diffusion-model/probe_src/depth_loss.py 25ba9b5031480973 ran MIT (permissive)
MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction 1 Jun 2022 autonomousvision/monosdf/code/model/loss.py 25ba9b5031480973 ran MIT (permissive)
GMFlow: Learning Optical Flow via Global Matching 26 Nov 2021 raymondwang987/nvds/infer_NVDS_dpt_bi.py d3e701ed2a0c860a unverified MIT (permissive)
Improving 360 Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised Learning 22 Sep 2021 yuniw18/Joint_360depth/losses.py 5b3c2efd696c69f4 unverified MIT (permissive)

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections