Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels
Authors: Zifu Wang, Xuefei Ning, Matthew Blaschko
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments show consistent improvements over the cross-entropy loss across 4 semantic segmentation datasets (Cityscapes, PASCAL VOC, ADE20K, Deep Globe Land) and 13 architectures, including classic CNNs and recent vision transformers. |
| Researcher Affiliation | Academia | Zifu Wang1 Xuefei Ning2 Matthew B. Blaschko1 1 ESAT-PSI, KU Leuven, Leuven, Belgium 2 Department of Electronic Engineering, Tsinghua University, Beijing, China |
| Pseudocode | Yes | Figure 6: Code to compute active classes. |
| Open Source Code | Yes | The code is available at https://github.com/zifuwanggg/JDTLosses. |
| Open Datasets | Yes | We evaluate models on Cityscapes [11], PASCAL VOC [18], ADE20K [81] and Deep Globe Land [12]. |
| Dataset Splits | Yes | For Cityscapes, PASCAL VOC, and ADE20K, we repeat the experiments 3 times (except for SSL experiments that are single runs) and report performance on the validation set. For Deep Globe Land, we conduct 5-fold cross-validation. |
| Hardware Specification | Yes | Inference latency measurements are conducted with the same input size on a NVIDIA A100. We estimate the training memory requirements using a ground-truth size of 8 19 512 1024 (batch_size, num_classes, H, W), also on a NVIDIA A100. |
| Software Dependencies | No | The paper mentions software like Pytorch Image Models (timm) and Adam W but does not provide specific version numbers for these dependencies. |
| Experiment Setup | Yes | By default, we adopted the training details outlined in [70, 23, 24], except for the reduction of the batch size to 8. In particular, we utilize SGD with a weight decay of 0.0005 and a momentum of 0.9. The initial learning rate is 0.01, and is decayed according to (1 iter total iters)0.9. The number of iterations is 40K for Cityscapes [11] and PASCAL VOC [18], 10K for Deep Globe Land [12]. The crop size is 512 1024 for Cityscapes [11], 512 512 for PASCAL VOC [18] and Deep Globe Land [12]. |