ALOV300++ Dataset
by 'Amsterdam Library of Ordinary Videos for evaluating visual trackers robustness'

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1 740 80 895 80 895 322 740 322 6 739.76 80.31 894.85 80.31 894.85 322.24 739.76 322.24 11 734.76 80.31 889.85 80.31 889.85 322.24 734.76 322.24 16 734.76 80.31 889.85 80.31 889.85 322.24 734.76 322.24 21 734.76 80.31 889.85 80.31 889.85 322.24 734.76 322.24 26 729.76 80.31 884.85 80.31 884.85 322.24 729.76 322.24 31 724.76 80.31 879.85 80.31 879.85 322.24 724.76 322.24 36 724.76 80.31 879.85 80.31 879.85 322.24 724.76 322.24 41 724.76 70.31 879.85 70.31 879.85 312.24 724.76 312.24 46 719.76 65.31 874.85 65.31 874.85 307.24 719.76 307.24 51 719.76 60.31 874.85 60.31 874.85 302.24 719.76 302.24 56 719.76 55.31 874.85 55.31 874.85 297.24 719.76 297.24 61 714.76 55.31 869.85 55.31 869.85 297.24 714.76 297.24 66 714.76 55.31 869.85 55.31 869.85 297.24 714.76 297.24 71 709.76 55.31 864.85 55.31 864.85 297.24 709.76 297.24 76 709.76 55.31 864.85 55.31 864.85 297.24 709.76 297.24 81 709.76 55.31 864.85 55.31 864.85 297.24 709.76 297.24 86 714.76 60.31 869.85 60.31 869.85 302.24 714.76 302.24 91 719.76 60.31 874.85 60.31 874.85 302.24 719.76 302.24 96 714.76 60.31 869.85 60.31 869.85 302.24 714.76 302.24 101 714.76 60.31 869.85 60.31 869.85 302.24 714.76 302.24 106 724.77 64.94 844.04 64.94 844.04 294.86 724.77 294.86 111 724.77 64.94 844.04 64.94 844.04 294.86 724.77 294.86 116 719.77 64.94 839.04 64.94 839.04 294.86 719.77 294.86 121 714.77 59.95 834.04 59.95 834.04 289.86 714.77 289.86 126 714.77 59.95 834.04 59.95 834.04 289.86 714.77 289.86 131 714.77 59.95 834.04 59.95 834.04 289.86 714.77 289.86 136 719.77 59.95 839.04 59.95 839.04 289.86 719.77 289.86 141 719.77 59.95 839.04 59.95 839.04 289.86 719.77 289.86 146 719.77 59.95 839.04 59.95 839.04 289.86 719.77 289.86 151 719.77 59.95 839.04 59.95 839.04 289.86 719.77 289.86 156 714.77 59.95 834.04 59.95 834.04 289.86 714.77 289.86 161 709.9 51.09 869.1 51.09 869.1 291.27 709.9 291.27 166 709.9 56.09 869.1 56.09 869.1 296.27 709.9 296.27 171 709.9 61.09 869.1 61.09 869.1 301.27 709.9 301.27 176 714.9 61.09 874.1 61.09 874.1 301.27 714.9 301.27 181 714.9 56.09 874.1 56.09 874.1 296.27 714.9 296.27 186 714.9 56.09 874.1 56.09 874.1 296.27 714.9 296.27 191 704.9 56.09 864.1 56.09 864.1 296.27 704.9 296.27 196 704.9 56.09 864.1 56.09 864.1 296.27 704.9 296.27 201 704.9 56.09 864.1 56.09 864.1 296.27 704.9 296.27 206 704.9 51.09 864.1 51.09 864.1 291.27 704.9 291.27 211 704.9 46.09 864.1 46.09 864.1 286.27 704.9 286.27 216 709.9 46.09 869.1 46.09 869.1 286.27 709.9 286.27 221 709.9 46.09 869.1 46.09 869.1 286.27 709.9 286.27 226 709.9 41.09 869.1 41.09 869.1 281.27 709.9 281.27 231 704.9 41.09 864.1 41.09 864.1 281.27 704.9 281.27 236 704.9 46.09 864.1 46.09 864.1 286.27 704.9 286.27 241 704.9 51.09 864.1 51.09 864.1 291.27 704.9 291.27 246 704.9 56.09 864.1 56.09 864.1 296.27 704.9 296.27 251 704.9 56.09 864.1 56.09 864.1 296.27 704.9 296.27 256 704.9 51.09 864.1 51.09 864.1 291.27 704.9 291.27 261 712.93 52.22 839.23 52.22 839.23 289.86 712.93 289.86 266 712.93 52.22 839.23 52.22 839.23 289.86 712.93 289.86 271 712.93 52.22 839.23 52.22 839.23 289.86 712.93 289.86 276 707.93 52.22 834.23 52.22 834.23 289.86 707.93 289.86 281 707.93 47.22 834.23 47.22 834.23 284.86 707.93 284.86 286 707.93 47.22 834.23 47.22 834.23 284.86 707.93 284.86 291 707.93 42.22 834.23 42.22 834.23 279.86 707.93 279.86 296 707.93 37.22 834.23 37.22 834.23 274.86 707.93 274.86 301 707.93 37.22 834.23 37.22 834.23 274.86 707.93 274.86 306 707.93 37.22 834.23 37.22 834.23 274.86 707.93 274.86 311 707.93 37.22 834.23 37.22 834.23 274.86 707.93 2