Code and Datasets for paper ["Optimizing Multi-task Network with Learned Prototypes for Weakly Supervised Semantic Segmentation"], submitted to Signal Processing: Image communication.
CAM: Link SeeNet: Link OAA+: Link PLLM: Link MLLM: Link MLPL:Link
By running the code: PRcurve/drawPR.m, you can reproduce the PR curves in Figure 9.
By running the code GTgeneration/CRFrefinementforGT.m, you can generate the proxy annotations on MLPL.
Run gen_gtwith_saliency maps.py. The saliency maps can be obtained from Link
By running Training code in the 2nd stage/main.py, the segmentation network will be optimized by the proxy annotations.