README.md

Fast, Accurate and Lightweight Super-Resolution models

We present FALSR A,B,C models. The metrics and results can be generated with,

Comparison with state-of-the-art methods

Method MulAdds Params Set5 Set14 BSD100 Urban100 SRCNN 52.7G 57K 36.66/0.9542 32.42/0.9063 31.36/0.8879 29.50/0.8946 FSRCNN 6.0G 12K 37.00/0.9558 32.63/0.9088 31.53/0.8920 29.88/0.9020 VDSR 612.6G 665K 37.53/0.9587 33.03/0.9124 31.90/0.8960 30.76/0.9140 DRCN 17,974.3G 1,774K 37.63/0.9588 33.04/0.9118 31.85/0.8942 30.75/0.9133 CNF 311.0G 337K 37.66/0.9590 33.38/0.9136 31.91/0.8962 - LapSRN 29.9G 813K 37.52/0.9590 33.08/0.9130 31.80/0.8950 30.41/0.9100 DRRN 6,796.9G 297K 37.74/0.9591 33.23/0.9136 32.05/0.8973 31.23/0.9188 BTSRN 207.7G 410K 37.75/- 33.20/- 32.05/- 31.63/- MemNet 2,662.4G 677K 37.78/0.9597 33.28/0.9142 32.08/0.8978 31.31/0.9195 SelNet 225.7G 974K 37.89/0.9598 33.61/0.9160 32.08/0.8984 - CARN 222.8G 1,592K 37.76/0.9590 33.52/0.9166 32.09/0.8978 31.92/0.9256 CARN-M 91.2G 412K 37.53/0.9583 33.26/0.9141 31.92/0.8960 31.23/0.9194 MoreMNAS-A 238.6G 1039K 37.63/0.9584 33.23/0.9138 31.95/0.8961 31.24/0.9187 MoreMNAS-B 256.9G 1118K 37.58/0.9584 33.22/0.9135 31.91/0.8959 31.14/0.9175 MoreMNAS-C 5.5G 25K 37.06/0.9561 32.75/0.9094 31.50/0.8904 29.92/0.9023 MoreMNAS-D 152.4G 664K 37.57/0.9584 33.25/0.9142 31.94/0.8966 31.25/0.9191 FALSR-A (ours) 234.7G 1,021K 37.82/0.9595 33.55/0.9168 32.12/0.8987 31.93/0.9256 FALSR-B (ours) 74.7G 326k 37.61/0.9585 33.29/0.9143 31.97/0.8967 31.28/0.9191 FALSR-C (ours) 93.7G 408k 37.66/0.9586 33.26/0.9140 31.96/0.8965 31.24/0.9187