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Benchmark

NOTE: all results are evaluated from retrained model here.

SISR (Single-Image Super-Resolution)*

Model	Scale Factor	Set5	Set14	BSD100	Urban100	Framework
Bicubic	x2	33.66/0.9299	30.24/0.8688	29.56/0.8431	26.88/0.8403	-
--------	-------------	------------	------------	------------	------------	-----------
Bicubic	x4	28.42/0.8104	26.00/0.7027	25.96/0.6675	23.14/0.6577	-
SRCNN	x4	30.03/0.8514	26.94/0.7453	26.70/0.7054	24.08/0.7048	PyTorch
ESPCN	x4	29.01/0.8324	26.38/0.7348	26.34/0.7002	23.62/0.6872	PyTorch
VDSR*	x4	28.39/0.8108	25.76/0.7056	25.95/0.6698	23.12/0.6591	PyTorch
DRCN	x4	30.90/0.8748	27.59/0.7650	27.11/0.7204	-/-	PyTorch
DRRN	x4	31.07/0.8771	27.62/0.7663	27.15/0.7221	24.94/0.7438	PyTorch
SRCNN	x4	29.78/0.8441	26.83/0.7409	26.61/0.7014	23.94/0.6984	Tensorflow
VDSR*	x4	28.38/0.8104	25.84/0.7054	25.95/0.6694	23.12/0.6590	Tensorflow

Training hyper-params:
- Steps: 40k
- Dataset: DIV2K
- Batch: [16,96,96,3] (HR)
VDSR seems fail to reach its global minima.

VSR (Video Super-Resolution)

Model	Scale	VID4	TBD..	TBD..	TBD..	Framework
Bicubic	x4	23.58/0.6363				-
Bayesian	x4	26.04/0.8151				Matlab
VESPCN-1	x4	25.46/0.7432				Tensorflow
VESPCN-3	x4	25.04/0.7143				PyTorch
SPMC	x4	25.65/0.7513				PyTorch
SOFVSR	x4	26.04/0.7753				PyTorch
FRVSR	x4	26.10/0.7755				PyTorch
RBPN	x4	26.23/0.7843				PyTorch

Compare Y-channel only, no border pixel shaved off.

Image Denoise

Model	AWGN Level	BSD68	Set12	Urban100
BM3D	15	31.08/0.8722	32.37/0.8952	32.35/0.9220
--------	------------	------------	------------	------------
BM3D	25	28.57/0.8013	29.97/0.8504	29.70/0.8777
--------	------------	------------	------------	------------
BM3D	50	25.62/0.6864	26.72/0.7676	25.95/0.7791

Degradation Image Super-Resolution

Model	Scale	AWGN	Set5	Set14	Urban100	BSD100
VDSR	x4	15	26.11/0.7400	24.01/0.6293	22.11/0.6365	24.23/0.6037
VDSR-B	x4	15	25.73/0.7232	23.63/0.6090	21.82/0.6196	24.03/0.5915
--------	-------	------	------------	------------	------------	------------
VDSR	x4	25	24.66/0.6912	22.93/0.5818	21.27/0.5915	23.35/0.5611
VDSR-B	x4	25	24.31/0.6729	22.50/0.5602	21.03/0.5742	23.13/0.5485
--------	-------	------	------------	------------	------------	------------
VDSR	x4	50	22.27/0.5977	20.92/0.5005	19.74/0.5049	21.73/0.4907
VDSR-B	x4	50	22.02/0.5811	20.52/0.4792	19.53/0.4862	21.53/0.4783

TF v.s. Torch (x4)

TF/Torch	Set5	Set14	BSD100	Urban100
Baseline	28.42	26.00	25.96	23.14

Winner: TF(), Torch()