paper-with-me

Object Counting 벤치마크

Object Counting on TallyQA-Complex

6개 결과 · ⬇ CSV · JSON

Accuracy

54.1 59.85 65.6 71.35 77.1 2018-10 2026-11 RCN — 56.2 (2018-10-29) MoVie-ResNeXt — 56.8 (2020-04-24) MoVie — 54.1 (2020-04-24) SMoLA-PaLI-X Specialist — 77.1 (2023-12-01) SMoLA-PaLI-X Generalist (0 shot) — 70.7 (2023-12-01) PaLI-X-VPD — 76.6 (2023-12-05) RCN — 56.2 (2018-10-29) MoVie-ResNeXt — 56.8 (2020-04-24) SMoLA-PaLI-X Specialist — 77.1 (2023-12-01)
RankModel AccuracyRMSE Extra Training Data PaperCodeYear
1 SMoLA-PaLI-X Specialist 77.1– ✓ Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts 2023
2 PaLI-X-VPD 76.6– Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models 2023
3 SMoLA-PaLI-X Generalist (0 shot) 70.7– ✓ Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts 2023
4 MoVie-ResNeXt 56.81.43 MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond facebookresearch/mmf 2020
5 RCN 56.21.43 TallyQA: Answering Complex Counting Questions manoja328/tallyqacode 2018
6 MoVie 54.11.52 MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond facebookresearch/mmf 2020
1–6 / 6 페이지당 10 20 50 100