Papers › Normal Assisted Stereo Depth Estimation

Normal Assisted Stereo Depth Estimation

24 Nov 2019CVPR 2020 6arXiv:1911.10444archive 2025-07-28

Uday Kusupati, Shuo Cheng, Rui Chen, Hao Su

Accurate stereo depth estimation plays a critical role in various 3D tasks in both indoor and outdoor environments. Recently, learning-based multi-view stereo methods have demonstrated competitive performance with a limited number of views. However, in challenging scenarios, especially when building cross-view correspondences is hard, these methods still cannot produce satisfying results. In this paper, we study how to leverage a normal estimation model and the predicted normal maps to improve the depth quality. We couple the learning of a multi-view normal estimation module and a multi-view depth estimation module. In addition, we propose a novel consistency loss to train an independent consistency module that refines the depths from depth/normal pairs. We find that the joint learning can improve both the prediction of normal and depth, and the accuracy & smoothness can be further improved by enforcing the consistency. Experiments on MVS, SUN3D, RGBD, and Scenes11 demonstrate the effectiveness of our method and state-of-the-art performance.

PaperPDFConference PDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="1911.10444")

Code

Syntology Ran 2 of 14 code samples harvested from 1 repository linked to this paper; 12 have no recorded run. Of those that ran: 1 ran · our draft was wrong; 1 ran with no contract checked.

By repository: official repository: 14 samples from 1 repository, 2 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

14 samples harvested; 2 ran; 0 honoured the contract we drafted; 12 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · our draft was wrong
1ran
12unverified

Licence: 0 of the 14 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from udaykusupati/Normal-Assisted-Stereo. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “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.

Each sample ends with its 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.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at 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 label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

convbn udaykusupati/Normal-Assisted-Stereo/models/submodule.py official repository ran · our draft was wrong MIT (permissive) · 15ab3c76823aef7e · report
convbn_3d udaykusupati/Normal-Assisted-Stereo/models/submodule.py official repository ran MIT (permissive) · 46674adf87c5459d · report
cal_normal udaykusupati/Normal-Assisted-Stereo/convert_normal.py official repository unverified MIT (permissive) · 4f163abd4dbd1459 · report
cam2pixel udaykusupati/Normal-Assisted-Stereo/inverse_warp.py official repository unverified MIT (permissive) · 2c4437fdbce873a5 · report
compute_angles udaykusupati/Normal-Assisted-Stereo/loss_functions.py official repository unverified MIT (permissive) · 8e71c9feb86fc2c3 · report
compute_errors_test udaykusupati/Normal-Assisted-Stereo/loss_functions.py official repository unverified MIT (permissive) · 3795ee04b993aecb · report
compute_errors_train udaykusupati/Normal-Assisted-Stereo/loss_functions.py official repository unverified MIT (permissive) · 56f26f9a1c756e3b · report
convtext udaykusupati/Normal-Assisted-Stereo/models/MVDNet.py official repository unverified MIT (permissive) · 12ea6024e74f0a0c · report
inverse_warp udaykusupati/Normal-Assisted-Stereo/inverse_warp.py official repository unverified MIT (permissive) · 7b9135ddb1bb3d08 · report
load_h5 udaykusupati/Normal-Assisted-Stereo/data_loader.py official repository unverified MIT (permissive) · e5e3810a24d68c24 · report
load_png udaykusupati/Normal-Assisted-Stereo/data_loader.py official repository unverified MIT (permissive) · ee3f64e2892afc0c · report
pixel2cam udaykusupati/Normal-Assisted-Stereo/inverse_warp.py official repository unverified MIT (permissive) · bcc0dab2c21a63a8 · report
pop3d udaykusupati/Normal-Assisted-Stereo/convert_normal.py official repository unverified MIT (permissive) · 03d5369cf263d580 · report
tensor2array udaykusupati/Normal-Assisted-Stereo/utils.py official repository unverified MIT (permissive) · 1dea398d0e1f7446 · report

Tasks

Depth EstimationStereo Depth Estimation

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

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