Papers › D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement

D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement

17 Oct 2024arXiv:2410.13842archive 2025-07-28

Yansong Peng, Hebei Li, Peixi Wu, Yueyi Zhang, Xiaoyan Sun, Feng Wu

We introduce D-FINE, a powerful real-time object detector that achieves outstanding localization precision by redefining the bounding box regression task in DETR models. D-FINE comprises two key components: Fine-grained Distribution Refinement (FDR) and Global Optimal Localization Self-Distillation (GO-LSD). FDR transforms the regression process from predicting fixed coordinates to iteratively refining probability distributions, providing a fine-grained intermediate representation that significantly enhances localization accuracy. GO-LSD is a bidirectional optimization strategy that transfers localization knowledge from refined distributions to shallower layers through self-distillation, while also simplifying the residual prediction tasks for deeper layers. Additionally, D-FINE incorporates lightweight optimizations in computationally intensive modules and operations, achieving a better balance between speed and accuracy. Specifically, D-FINE-L / X achieves 54.0% / 55.8% AP on the COCO dataset at 124 / 78 FPS on an NVIDIA T4 GPU. When pretrained on Objects365, D-FINE-L / X attains 57.1% / 59.3% AP, surpassing all existing real-time detectors. Furthermore, our method significantly enhances the performance of a wide range of DETR models by up to 5.3% AP with negligible extra parameters and training costs. Our code and pretrained models: https://github.com/Peterande/D-FINE.

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="2410.13842")

Code

Syntology Ran 10 of 14 code samples harvested from 1 repository linked to this paper; 4 have no recorded run. Of those that ran: 10 ran with no contract checked.

By repository: official repository: 14 samples from 1 repository, 10 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

Peterande/D-FINE officialmentioned in papermentioned on GitHubpytorchApache-2.0 report
open-edge-platform/geti mentioned on GitHubpytorchApache-2.0 report
shihuahuang95/deim mentioned on GitHubpytorchNOASSERTION 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

14 samples harvested; 10 ran; 0 honoured the contract we drafted; 4 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.

10ran
4unverified

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 Peterande/D-FINE. “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.

dictify Peterande/D-FINE/src/core/yaml_utils.py official repository ran fingerprinted Apache-2.0 (permissive) · 55ac89cb59e7fe93 · report
elementwise_box_iou Peterande/D-FINE/src/misc/box_ops.py official repository ran fingerprinted Apache-2.0 (permissive) · f032fa04460c4fc9 · report
elementwise_generalized_box_iou Peterande/D-FINE/src/misc/box_ops.py official repository ran fingerprinted Apache-2.0 (permissive) · 96986c2e89b1597c · report
extract_schema Peterande/D-FINE/src/core/workspace.py official repository ran Apache-2.0 (permissive) · 1202e5e128785814 · report
generalized_box_iou Peterande/D-FINE/src/misc/box_ops.py official repository ran fingerprinted Apache-2.0 (permissive) · 2f52077940b53c42 · report
load_config Peterande/D-FINE/src/core/yaml_utils.py official repository ran Apache-2.0 (permissive) · 024f9ddd58b25511 · report
merge_dict Peterande/D-FINE/src/core/yaml_utils.py official repository ran Apache-2.0 (permissive) · 288efb4f48e3358a · report
register Peterande/D-FINE/src/core/workspace.py official repository ran Apache-2.0 (permissive) · 2a50c87f96494841 · report
setup_distributed Peterande/D-FINE/src/misc/dist_utils.py official repository ran Apache-2.0 (permissive) · a65eab71a65df60e · report
warp_model Peterande/D-FINE/src/misc/dist_utils.py official repository ran Apache-2.0 (permissive) · 18349a0bf298c043 · report
all_gather Peterande/D-FINE/src/misc/logger.py official repository unverified Apache-2.0 (permissive) · 0216311af005f21f · report
create Peterande/D-FINE/src/core/workspace.py official repository unverified Apache-2.0 (permissive) · eb5e01d60557539c · report
de_model Peterande/D-FINE/src/misc/dist_utils.py official repository unverified Apache-2.0 (permissive) · 8c4ff9fb866ea191 · report
reduce_dict Peterande/D-FINE/src/misc/logger.py official repository unverified Apache-2.0 (permissive) · e6c2f1b16c9d4813 · report

Tasks

Real-Time Object Detectionregression

1 archive task tag without a task page not shown.

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-X+ FPS (V100, b=1) 78 (T4) #2 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-X+ box AP 59.3 #2 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-X FPS (V100, b=1) 78 (T4) #11 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-X box AP 55.8 #11 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-M+ FPS (V100, b=1) 178 (T4) #15 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-M+ box AP 55.1 #15 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-L FPS (V100, b=1) 124 (T4) #26 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-L box AP 54.0 #26 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-M FPS (V100, b=1) 178 (T4) #45 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-M box AP 52.3 #45 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-S+ FPS (V100, b=1) 287 (T4) #54 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-S+ box AP 50.7 #54 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-S FPS (V100, b=1) 287 (T4) #61 of 82 Archive leaderboard report
Real-Time Object Detection COCO (Common Objects in Context) D-FINE-S box AP 48.5 #61 of 82 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

Absolute Position EncodingsAdamAttentionBPEConvolutionDense ConnectionsDetrDropoutFeedforward NetworkLabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSPEEDSoftmaxTransformer

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