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Published at November 29LDA-AQU: Adaptive Query-guided Upsampling via Local Deformable Attention
cs.CV
cs.LG
Released Date: November 29, 2024
Authors: Zewen Du1, Zhenjiang Hu1, Guiyu Zhao1, Ying Jin1, Hongbin Ma1
Aff.: 1Beijing Institute of Technology, Beijing, China

| Faster R-CNN | Backbone | Params | FLOPs | Reference | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Nearest | ResNet-50 | 37.5 | 58.2 | 40.8 | 21.3 | 41.1 | 48.9 | 46.8M | 208.5G | - |
| Deconv | ResNet-50 | 37.3 | 57.8 | 40.3 | 21.3 | 41.1 | 48.0 | +2.4M | +12.6G | - |
| PS (Shi et al., 2016) | ResNet-50 | 37.5 | 58.5 | 40.4 | 21.5 | 41.5 | 48.3 | +9.4M | +50.2G | CVPR16 |
| CARAFE (Wang et al., 2019) | ResNet-50 | 38.6 | 59.9 | 42.2 | 23.3 | 42.2 | 49.7 | +0.3M | +1.6G | ICCV19 |
| IndexNet (Lu et al., 2019) | ResNet-50 | 37.6 | 58.4 | 40.9 | 21.5 | 41.3 | 49.2 | +8.4M | +46.4G | ICCV19 |
| A2U (Dai et al., 2021) | ResNet-50 | 37.3 | 58.7 | 40.0 | 21.7 | 41.1 | 48.5 | +38.9K | +0.3G | CVPR21 |
| FADE (Lu et al., 2022a) | ResNet-50 | 38.5 | 59.6 | 41.8 | 23.1 | 42.2 | 49.3 | +0.2M | +3.4G | ECCV22 |
| SAPA-B (Lu et al., 2022b) | ResNet-50 | 37.8 | 59.2 | 40.6 | 22.4 | 41.4 | 49.1 | +0.1M | +2.4G | NeurIPS22 |
| DySample (Liu et al., 2023) | ResNet-50 | 38.7 | 60.0 | 42.2 | 22.5 | 42.4 | 50.2 | +65.5K | +0.3G | ICCV23 |
| LDA-AQU* | ResNet-50 | 38.9 | 60.4 | 42.4 | 23.3 | 42.8 | 49.7 | +41.0K | +0.4G | - |
| LDA-AQU | ResNet-50 | 39.2 | 60.7 | 42.7 | 22.9 | 43.0 | 50.1 | +0.2M | +1.7G | - |