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Update README with LTDETRv2 m/l benchmark results#894

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Update README with LTDETRv2 m/l benchmark results#894
gabrielfruet wants to merge 3 commits into
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gabriel-trn-2325-update-readme-for-ltdetrv2-object-detection-with-new

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@gabrielfruet gabrielfruet commented Jul 21, 2026

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Depends on: #887 (must merge first or together — the m/l -coco aliases don't exist until then)

What has changed and why?

ltdetrv2-s-coco was the only LTDETRv2 size with published COCO numbers in
the README. Adds ltdetrv2-m-coco (53.1 mAP) and ltdetrv2-l-coco (56.0 mAP),
plus T4 latency for all three sizes from internal benchmarking.

Checkpoint uploads for m/l (wiring the -coco aliases to downloadable
checkpoints) are tracked in a separate PR — this one only updates the
benchmark table.

How has it been tested?

README-only change; visually checked the rendered table for alignment.

Did you update CHANGELOG.md?

  • Yes
  • Not needed (internal change)

Did you update the documentation?

  • Yes
  • Not needed (internal change without effects for user)

s-coco was the only LTDETRv2 size with published COCO numbers. Add
m and l (53.1 / 56.0 mAP) with T4 latency from the LT-DETRv2 latency
benchmark; x is still training so its mAP is marked TBD. Checkpoint
uploads for m/l/x are tracked separately.
@gabrielfruet gabrielfruet changed the title Update README with LTDETRv2 m/l/x benchmark results Update README with LTDETRv2 m/l benchmark results Jul 24, 2026
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/codex review

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/review

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gabrielfruet marked this pull request as ready for review July 24, 2026 14:41

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Comment thread README.md

@yutong-xiang-97 yutong-xiang-97 left a comment

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We can add a plot here and compare with the competitor models!

Comment thread README.md
@@ -95,6 +93,8 @@ Train LTDETR detection models with DINOv2, DINOv3, or EdgeCrafter ECViT backbone
| picodet-s-coco | 26.7\* | 2.2\* | 1.17 | 416×416 |

@yutong-xiang-97 yutong-xiang-97 Jul 24, 2026

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I would actually want to drop picodet numbers or move it to the bottom but I will leave it to you to decide.

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Or alternatively, group the results with model backbones. I think up to this point the table is a bit too long to read.

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I think it makes more sense to drop picodet

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