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FFA-Net: Feature Fusion Attention Network for Single Image Dehazing

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I believe that if you use the global residual connection, you need to normalize both of them. Unless, the residual term has to learn much more complicated space.

这论文竟然对真实有雾图几乎没用

Thanks for sharing your great work! I am a collector of great models. I basically collect models in the repositories below with the consent of the model authors, convert them...

Hi, thank you for releasing the code and pre-trained models. When I test the pre-trained model ('its_train_ffa_3_19.pk') downloaded from the released website, I got "loading state_dict for DataParallel: Unexpected key(s)...

I used your code to train and test on RESIDE V0 dataset but I got the result 0.84/20.57 (SSIM/PSNR) for indoor task. Was I wrong at any step?

Hello, I train the network on my server according to your training method, the effect is very different, PSNR = 12.52, SSIM = 0.3597. What is the reason for this.

请问如何测试处理单张图片的时间?

提示内存不够,我在任务管理器中看了内存条32g的确是将近满了,CPU90%以上,我有两个GPU,GPU0是Intel(R) HD Graphics 630约30%,GPU1是NVIDIA GeForce GTX 1050 Ti2%基本没变化,我感觉我NVIDIA显卡没派上用场,你的电脑配置是什么样的跑成功了吗,你是使用什么软件运行这个代码的?

D:\python\envs\pytorch\python.exe E:/FFA-Net-master/net/main.py Namespace(blocks=20, bs=16, crop=False, crop_size=240, device='cpu', eval_step=5000, gps=3, lr=0.0001, model_dir='./trained_models/its_train_ffa_3_20.pk', net='ffa', no_lr_sche=False, perloss=False, resume=True, steps=100000, testset='its_test', trainset='its_train') model_dir: ./trained_models/its_train_ffa_3_20.pk 16 E:\FFA-Net-master\net crop size whole_img crop size whole img crop...

Why is there a big difference between the same picture using the PSNR and SSIM methods here and the method provided on the RESIDE official website? What caused it?