Papers › Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization

Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization

22 Jun 2022arXiv:2206.11134archive 2025-07-28

Peixian Chen, Kekai Sheng, Mengdan Zhang, Mingbao Lin, Yunhang Shen, Shaohui Lin, Bo Ren, Ke Li

Open-vocabulary object detection (OVD) aims to scale up vocabulary size to detect objects of novel categories beyond the training vocabulary. Recent work resorts to the rich knowledge in pre-trained vision-language models. However, existing methods are ineffective in proposal-level vision-language alignment. Meanwhile, the models usually suffer from confidence bias toward base categories and perform worse on novel ones. To overcome the challenges, we present MEDet, a novel and effective OVD framework with proposal mining and prediction equalization. First, we design an online proposal mining to refine the inherited vision-semantic knowledge from coarse to fine, allowing for proposal-level detection-oriented feature alignment. Second, based on causal inference theory, we introduce a class-wise backdoor adjustment to reinforce the predictions on novel categories to improve the overall OVD performance. Extensive experiments on COCO and LVIS benchmarks verify the superiority of MEDet over the competing approaches in detecting objects of novel categories, e.g., 32.6% AP50 on COCO and 22.4% mask mAP on LVIS.

PaperPDFCodeCode 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="2206.11134")

Code

Syntology Ran 7 of 9 code samples harvested from 1 repository linked to this paper; 2 have no recorded run. Of those that ran: 1 ran · violated contract; 1 ran · our draft was wrong; 2 ran · fixture could not drive it; 3 ran with no contract checked.

By repository: official repository: 9 samples from 1 repository, 7 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

pealing/medet officialmentioned in paperpytorchApache-2.0 report
peixianchen/medet officialmentioned in paperpytorchApache-2.0 report

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

9 samples harvested; 7 ran; 0 honoured the contract we drafted; 2 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 · violated contract
1ran · our draft was wrong
2ran · fixture could not drive it
3ran
2unverified

Licence: 0 of the 9 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 pealing/medet. “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.

get_clip_embeddings pealing/medet/medet/predictor.py official repository ran Apache-2.0 (permissive) · 1f211df98dc51cee · report
get_fed_loss_inds pealing/medet/medet/modeling/utils.py official repository ran Apache-2.0 (permissive) · bb583e07209fe58b · report
load_class_freq pealing/medet/medet/modeling/utils.py official repository ran Apache-2.0 (permissive) · 1f6e4c3da7b82979 · report
match_name_keywords pealing/medet/medet/custom_solver.py official repository ran · violated contract Apache-2.0 (permissive) · c15434906f804d7f · report
permute_to_N_HWA_K pealing/medet/medet/modeling/meta_arch/dense_detector.py official repository ran · fixture could not drive it fingerprinted Apache-2.0 (permissive) · 573ab018aa3f2e6f · report
window_partition pealing/medet/medet/modeling/backbone/swintransformer.py official repository ran · fixture could not drive it fingerprinted Apache-2.0 (permissive) · f9fd6241d935f07b · report
window_reverse pealing/medet/medet/modeling/backbone/swintransformer.py official repository ran · our draft was wrong Apache-2.0 (permissive) · fb32094c6dbece71 · report
compute_average_precision pealing/medet/medet/evaluation/oideval.py official repository unverified Apache-2.0 (permissive) · 2e0a799ccbd489e7 · report
create_timm_resnet pealing/medet/medet/modeling/backbone/timm.py official repository unverified Apache-2.0 (permissive) · 625ac447e2e8b2bc · report

Tasks

Causal InferenceObject DetectionOpen Vocabulary Object DetectionOpen-vocabulary object detectionobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Open Vocabulary Object Detection LVIS v1.0 MEDet AP novel-LVIS base training 22.4 #18 of 28 Archive leaderboard report
Open Vocabulary Object Detection MSCOCO MEDet (RN50) AP 0.5 32.6 #22 of 32 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

BASE

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