├── LICENSE ├── README.md ├── datasets ├── example_imgs_ade │ ├── ADE_val_00000876.jpg │ ├── ADE_val_00001067.jpg │ ├── ADE_val_00001517.jpg │ ├── ADE_val_00001586.jpg │ ├── ADE_val_00001766.jpg │ └── ADE_val_00001871.jpg ├── example_imgs_cityscapes │ ├── munster_000098_000019.png │ └── munster_000150_000019.png ├── example_imgs_nyud │ ├── 000775.png │ ├── 001280.png │ └── 001431.png ├── example_imgs_pascalcontext │ ├── 2008_004203.jpg │ ├── 2009_001044.jpg │ ├── 2009_001196.jpg │ ├── 2009_004129.jpg │ ├── 2010_000743.jpg │ ├── 2010_000928.jpg │ ├── 2010_001036.jpg │ ├── 2010_005731.jpg │ └── 2010_005788.jpg ├── example_imgs_person_parts │ ├── 2008_001138.jpg │ ├── 2008_002932.jpg │ ├── 2008_004417.jpg │ ├── 2008_005552.jpg │ ├── 2008_008469.jpg │ ├── 2010_002927.jpg │ ├── 2010_005079.jpg │ ├── 2010_005626.jpg │ ├── 2011_001425.jpg │ └── 2011_003093.jpg ├── example_imgs_sunrgbd │ ├── 12.jpg │ ├── 1575.jpg │ ├── 215.jpg │ ├── 2183.jpg │ ├── 2185.jpg │ ├── 226.jpg │ ├── 234.jpg │ ├── 235.jpg │ ├── 255.jpg │ ├── 728.jpg │ ├── 91.jpg │ └── 95.jpg └── example_imgs_voc │ ├── 2007_001311.jpg │ ├── 2007_001457.jpg │ ├── 2007_001763.jpg │ ├── 2007_002094.jpg │ ├── 2007_005107.jpg │ ├── 2007_005844.jpg │ ├── 2007_006449.jpg │ ├── 2007_008815.jpg │ ├── 2007_009346.jpg │ ├── 2008_001138.jpg │ ├── 2009_003576.jpg │ ├── 2009_003703.jpg │ ├── 2011_001425.jpg │ └── 2011_003093.jpg ├── libs └── matconvnet │ ├── .gitattributes │ ├── .gitignore │ ├── .gitmodules │ ├── CONTRIBUTING.md │ ├── COPYING │ ├── Makefile │ ├── README.md │ ├── clone_date_26_Dec_2016.txt │ ├── doc │ ├── Makefile │ ├── blocks.tex │ ├── figures │ │ ├── imnet.pdf │ │ ├── pepper.pdf │ │ └── svg │ │ │ ├── conv.svg │ │ │ ├── convt.svg │ │ │ ├── matconvnet-blue.svg │ │ │ └── matconvnet-white.svg │ ├── fundamentals.tex │ ├── geometry.tex │ ├── impl.tex │ ├── intro.tex │ ├── matconvnet-manual.tex │ ├── matdoc.py │ ├── matdocparser.py │ ├── references.bib │ ├── site │ │ ├── docs │ │ │ ├── about.md │ │ │ ├── css │ │ │ │ └── fixes.css │ │ │ ├── developers.md │ │ │ ├── faq.md │ │ │ ├── figures │ │ │ │ ├── stn-perf.png │ │ │ │ └── stn-samples.png │ │ │ ├── functions.md │ │ │ ├── gpu.md │ │ │ ├── index.md │ │ │ ├── install-alt.md │ │ │ ├── install.md │ │ │ ├── js │ │ │ │ ├── mathjaxhelper.js │ │ │ │ └── toggle.js │ │ │ ├── pretrained.md │ │ │ ├── quick.md │ │ │ ├── spatial-transformer.md │ │ │ ├── training.md │ │ │ └── wrappers.md │ │ ├── mkdocs.yml │ │ └── theme │ │ │ ├── base.html │ │ │ ├── content.html │ │ │ ├── css │ │ │ └── base.css │ │ │ ├── js │ │ │ └── base.js │ │ │ ├── matconvnet-blue.svg │ │ │ ├── nav.html │ │ │ └── toc.html │ └── wrappers.tex │ ├── examples │ ├── cifar │ │ ├── cnn_cifar.m │ │ ├── cnn_cifar_init.m │ │ └── cnn_cifar_init_nin.m │ ├── cnn_train.m │ ├── cnn_train_dag.m │ ├── fast_rcnn │ │ ├── +dagnn │ │ │ └── LossSmoothL1.m │ │ ├── 000004.jpg │ │ ├── 000004_boxes.mat │ │ ├── README.md │ │ ├── bbox_functions │ │ │ ├── bbox_clip.m │ │ │ ├── bbox_draw.m │ │ │ ├── bbox_nms.m │ │ │ ├── bbox_overlap.m │ │ │ ├── bbox_remove_duplicates.m │ │ │ ├── bbox_scale.m │ │ │ ├── bbox_transform.m │ │ │ └── bbox_transform_inv.m │ │ ├── datasets │ │ │ ├── add_bboxreg_targets.m │ │ │ ├── attach_proposals.m │ │ │ ├── cnn_setup_data_voc07.m │ │ │ └── cnn_setup_data_voc07_ssw.m │ │ ├── fast_rcnn_demo.m │ │ ├── fast_rcnn_eval_get_batch.m │ │ ├── fast_rcnn_evaluate.m │ │ ├── fast_rcnn_init.m │ │ ├── fast_rcnn_train.m │ │ └── fast_rcnn_train_get_batch.m │ ├── imagenet │ │ ├── cnn_imagenet.m │ │ ├── cnn_imagenet_camdemo.m │ │ ├── cnn_imagenet_deploy.m │ │ ├── cnn_imagenet_evaluate.m │ │ ├── cnn_imagenet_googlenet.m │ │ ├── cnn_imagenet_init.m │ │ ├── cnn_imagenet_init_inception.m │ │ ├── cnn_imagenet_init_resnet.m │ │ ├── cnn_imagenet_minimal.m │ │ ├── cnn_imagenet_setup_data.m │ │ ├── cnn_imagenet_sync_labels.m │ │ ├── getImageBatch.m │ │ └── getImageStats.m │ ├── mnist │ │ ├── cnn_mnist.m │ │ ├── cnn_mnist_experiments.m │ │ └── cnn_mnist_init.m │ ├── spatial_transformer │ │ ├── cnn_stn_cluttered_mnist.m │ │ ├── cnn_stn_cluttered_mnist_init.m │ │ └── readme.txt │ └── vggfaces │ │ └── cnn_vgg_faces.m │ ├── matconvnet.sln │ ├── matconvnet.vcxproj │ ├── matconvnet.vcxproj.filters │ ├── matconvnet.xcodeproj │ ├── project.pbxproj │ ├── project.xcworkspace │ │ └── contents.xcworkspacedata │ └── xcshareddata │ │ └── xcschemes │ │ ├── matconv CPU.xcscheme │ │ ├── matconv GPU.xcscheme │ │ └── matconv cuDNN.xcscheme │ ├── matlab │ ├── +dagnn │ │ ├── @DagNN │ │ │ ├── DagNN.m │ │ │ ├── addLayer.m │ │ │ ├── do_backward_trn.m │ │ │ ├── do_forward_trn.m │ │ │ ├── eval.m │ │ │ ├── fromSimpleNN.m │ │ │ ├── getVarReceptiveFields.m │ │ │ ├── getVarSizes.m │ │ │ ├── initParams.m │ │ │ ├── loadobj.m │ │ │ ├── move.m │ │ │ ├── print.m │ │ │ ├── rebuild.m │ │ │ ├── removeLayer.m │ │ │ ├── renameLayer.m │ │ │ ├── renameVar.m │ │ │ ├── reset.m │ │ │ ├── saveobj.m │ │ │ ├── setLayerInputs.m │ │ │ ├── setLayerOutputs.m │ │ │ └── setLayerParams.m │ │ ├── AffineGridGenerator.m │ │ ├── BatchNorm.m │ │ ├── BatchNorm_bak.m │ │ ├── BilinearSampler.m │ │ ├── Concat.m │ │ ├── Conv.m │ │ ├── ConvTranspose.m │ │ ├── Crop.m │ │ ├── DropOut.m │ │ ├── ElementWise.m │ │ ├── Filter.m │ │ ├── LRN.m │ │ ├── Layer.m │ │ ├── Loss.m │ │ ├── NormOffset.m │ │ ├── Pooling.m │ │ ├── ROIPooling.m │ │ ├── ReLU.m │ │ ├── Scale.m │ │ ├── Sigmoid.m │ │ ├── SoftMax.m │ │ ├── SpatialNorm.m │ │ ├── Sum.m │ │ └── UniformScalingGridGenerator.m │ ├── ParameterServer.m │ ├── compatibility │ │ └── parallel │ │ │ ├── gather.m │ │ │ ├── labindex.m │ │ │ └── numlabs.m │ ├── mex │ │ ├── vl_cudatool.mexa64 │ │ ├── vl_imreadjpeg.mexa64 │ │ ├── vl_imreadjpeg_old.mexa64 │ │ ├── vl_nnbilinearsampler.mexa64 │ │ ├── vl_nnbnorm.mexa64 │ │ ├── vl_nnconv.mexa64 │ │ ├── vl_nnconvt.mexa64 │ │ ├── vl_nnnormalize.mexa64 │ │ ├── vl_nnpool.mexa64 │ │ ├── vl_nnroipool.mexa64 │ │ ├── vl_taccummex.mexa64 │ │ └── vl_tmove.mexa64 │ ├── simplenn │ │ ├── vl_simplenn.m │ │ ├── vl_simplenn_diagnose.m │ │ ├── vl_simplenn_display.m │ │ ├── vl_simplenn_move.m │ │ ├── vl_simplenn_start_parserv.m │ │ └── vl_simplenn_tidy.m │ ├── src │ │ ├── bits │ │ │ ├── data.cpp │ │ │ ├── data.cu │ │ │ ├── data.hpp │ │ │ ├── datacu.cu │ │ │ ├── datacu.hpp │ │ │ ├── datamex.cpp │ │ │ ├── datamex.cu │ │ │ ├── datamex.hpp │ │ │ ├── impl │ │ │ │ ├── bilinearsampler.hpp │ │ │ │ ├── bilinearsampler_cpu.cpp │ │ │ │ ├── bilinearsampler_gpu.cu │ │ │ │ ├── blashelper.hpp │ │ │ │ ├── bnorm.hpp │ │ │ │ ├── bnorm_cpu.cpp │ │ │ │ ├── bnorm_gpu.cu │ │ │ │ ├── compat.h │ │ │ │ ├── copy.hpp │ │ │ │ ├── copy_cpu.cpp │ │ │ │ ├── copy_gpu.cu │ │ │ │ ├── cudnnhelper.hpp │ │ │ │ ├── fast_mutex.h │ │ │ │ ├── im2row.hpp │ │ │ │ ├── im2row_cpu.cpp │ │ │ │ ├── im2row_gpu.cu │ │ │ │ ├── imread_gdiplus.cpp │ │ │ │ ├── imread_helpers.hpp │ │ │ │ ├── imread_libjpeg.cpp │ │ │ │ ├── imread_quartz.cpp │ │ │ │ ├── nnbias_blas.hpp │ │ │ │ ├── nnbias_cudnn.cu │ │ │ │ ├── nnbias_cudnn.hpp │ │ │ │ ├── nnbilinearsampler_cudnn.cu │ │ │ │ ├── nnbilinearsampler_cudnn.hpp │ │ │ │ ├── nnbnorm_cudnn.cu │ │ │ │ ├── nnbnorm_cudnn.hpp │ │ │ │ ├── nnconv_blas.hpp │ │ │ │ ├── nnconv_cudnn.cu │ │ │ │ ├── nnconv_cudnn.hpp │ │ │ │ ├── nnpooling_cudnn.cu │ │ │ │ ├── nnpooling_cudnn.hpp │ │ │ │ ├── normalize.hpp │ │ │ │ ├── normalize_cpu.cpp │ │ │ │ ├── normalize_gpu.cu │ │ │ │ ├── pooling.hpp │ │ │ │ ├── pooling_cpu.cpp │ │ │ │ ├── pooling_gpu.cu │ │ │ │ ├── roipooling.hpp │ │ │ │ ├── roipooling_cpu.cpp │ │ │ │ ├── roipooling_gpu.cu │ │ │ │ ├── sharedmem.cuh │ │ │ │ ├── subsample.hpp │ │ │ │ ├── subsample_cpu.cpp │ │ │ │ ├── subsample_gpu.cu │ │ │ │ ├── tinythread.cpp │ │ │ │ └── tinythread.h │ │ │ ├── imread.cpp │ │ │ ├── imread.hpp │ │ │ ├── mexutils.h │ │ │ ├── nnbias.cpp │ │ │ ├── nnbias.cu │ │ │ ├── nnbias.hpp │ │ │ ├── nnbilinearsampler.cpp │ │ │ ├── nnbilinearsampler.cu │ │ │ ├── nnbilinearsampler.hpp │ │ │ ├── nnbnorm.cpp │ │ │ ├── nnbnorm.cu │ │ │ ├── nnbnorm.hpp │ │ │ ├── nnconv.cpp │ │ │ ├── nnconv.cu │ │ │ ├── nnconv.hpp │ │ │ ├── nnfullyconnected.cpp │ │ │ ├── nnfullyconnected.cu │ │ │ ├── nnfullyconnected.hpp │ │ │ ├── nnnormalize.cpp │ │ │ ├── nnnormalize.cu │ │ │ ├── nnnormalize.hpp │ │ │ ├── nnpooling.cpp │ │ │ ├── nnpooling.cu │ │ │ ├── nnpooling.hpp │ │ │ ├── nnroipooling.cpp │ │ │ ├── nnroipooling.cu │ │ │ ├── nnroipooling.hpp │ │ │ ├── nnsubsample.cpp │ │ │ ├── nnsubsample.cu │ │ │ └── nnsubsample.hpp │ │ ├── config │ │ │ ├── mex_CUDA_glnxa64.sh │ │ │ ├── mex_CUDA_glnxa64.xml │ │ │ ├── mex_CUDA_maci64.sh │ │ │ └── mex_CUDA_maci64.xml │ │ ├── vl_cudatool.cpp │ │ ├── vl_cudatool.cu │ │ ├── vl_imreadjpeg.cpp │ │ ├── vl_imreadjpeg.cu │ │ ├── vl_imreadjpeg_old.cpp │ │ ├── vl_imreadjpeg_old.cu │ │ ├── vl_nnbilinearsampler.cpp │ │ ├── vl_nnbilinearsampler.cu │ │ ├── vl_nnbnorm.cpp │ │ ├── vl_nnbnorm.cu │ │ ├── vl_nnconv.cpp │ │ ├── vl_nnconv.cu │ │ ├── vl_nnconvt.cpp │ │ ├── vl_nnconvt.cu │ │ ├── vl_nnnormalize.cpp │ │ ├── vl_nnnormalize.cu │ │ ├── vl_nnpool.cpp │ │ ├── vl_nnpool.cu │ │ ├── vl_nnroipool.cpp │ │ ├── vl_nnroipool.cu │ │ ├── vl_taccummex.cpp │ │ ├── vl_taccummex.cu │ │ ├── vl_tmove.cpp │ │ └── vl_tmove.cu │ ├── vl_argparse.m │ ├── vl_compilenn.m │ ├── vl_imreadjpeg.m │ ├── vl_nnbilinearsampler.m │ ├── vl_nnbnorm.m │ ├── vl_nnconcat.m │ ├── vl_nnconv.m │ ├── vl_nnconvt.m │ ├── vl_nncrop.m │ ├── vl_nndropout.m │ ├── vl_nnloss.m │ ├── vl_nnnoffset.m │ ├── vl_nnnormalize.m │ ├── vl_nnnormalizelp.m │ ├── vl_nnpdist.m │ ├── vl_nnpool.m │ ├── vl_nnrelu.m │ ├── vl_nnroipool.m │ ├── vl_nnsigmoid.m │ ├── vl_nnsoftmax.m │ ├── vl_nnsoftmaxloss.m │ ├── vl_nnspnorm.m │ ├── vl_rootnn.m │ ├── vl_setupnn.m │ ├── vl_taccum.m │ ├── vl_tmove.m │ └── xtest │ │ ├── cmyk.jpg │ │ ├── suite │ │ ├── Scale.m │ │ ├── nnbilinearsampler.m │ │ ├── nnbnorm.m │ │ ├── nnconcat.m │ │ ├── nnconv.m │ │ ├── nnconvt.m │ │ ├── nndagnn.m │ │ ├── nndropout.m │ │ ├── nnloss.m │ │ ├── nnmnist.m │ │ ├── nnnormalize.m │ │ ├── nnnormalizelp.m │ │ ├── nnoffset.m │ │ ├── nnpdist.m │ │ ├── nnpool.m │ │ ├── nnrelu.m │ │ ├── nnroipool.m │ │ ├── nnsigmoid.m │ │ ├── nnsimplenn.m │ │ ├── nnsoftmax.m │ │ ├── nnsoftmaxloss.m │ │ ├── nnspnorm.m │ │ ├── nntest.m │ │ └── tmovemex.m │ │ ├── vl_bench_bnorm.m │ │ ├── vl_bench_imreadjpeg.m │ │ ├── vl_nnbnorm_old.m │ │ ├── vl_test_bnorm.m │ │ ├── vl_test_economic_relu.m │ │ ├── vl_test_gpureset.m │ │ ├── vl_test_imreadjpeg.m │ │ ├── vl_test_print.m │ │ └── vl_testnn.m │ └── utils │ ├── evaluate_ref_models.m │ ├── get-file.sh │ ├── import-caffe.py │ ├── import-fast-rcnn.sh │ ├── import-fcn.sh │ ├── import-googlenet.sh │ ├── import-ref-models.sh │ ├── import-resnet.sh │ ├── layers.py │ ├── model2dot.m │ ├── preprocess-imagenet.sh │ ├── proto │ ├── __init__.py │ ├── caffe.proto │ ├── caffe_0115.proto │ ├── caffe_0115_pb2.py │ ├── caffe_6e3916.proto │ ├── caffe_6e3916_pb2.py │ ├── caffe_b590f1d.proto │ ├── caffe_b590f1d_pb2.py │ ├── caffe_fastrcnn.proto │ ├── caffe_fastrcnn_pb2.py │ ├── caffe_old.proto │ ├── caffe_old_pb2.py │ ├── caffe_pb2.py │ ├── get-protos.sh │ ├── googlenet_prototxt_patch.diff │ ├── vgg_caffe.proto │ ├── vgg_caffe_pb2.py │ └── vgg_synset_words.txt │ ├── simplenn_caffe_compare.m │ ├── simplenn_caffe_deploy.m │ ├── simplenn_caffe_testdeploy.m │ ├── test_examples.m │ └── tidy_ref_models.m ├── main ├── My_concat_layer.m ├── My_copy_layer.m ├── My_net_util.m ├── My_sum_layer.m ├── My_util_dagnn.m ├── VOClabelcolormap.m ├── batch_do_data_augmentation.m ├── batch_do_data_crop.m ├── cat_str.m ├── check_do_bp_current_net.m ├── check_valid_net_output.m ├── cityscape_cmap.mat ├── class_info_ADE.mat ├── cnn_batch_info_disp.m ├── cnn_epoch_evaluate.m ├── cnn_forward_evaluate_obj.m ├── cnn_global_init_fn.m ├── cnn_layer_dagnn_wrapper_backward.m ├── cnn_layer_dagnn_wrapper_forward.m ├── cnn_layer_dense_softmaxloss_backward.m ├── cnn_layer_dense_softmaxloss_forward.m ├── cnn_layer_dummy_backward.m ├── cnn_layer_dummy_forward.m ├── cnn_layer_path_merge_backward.m ├── cnn_layer_path_merge_forward.m ├── cnn_load_model.m ├── cnn_loss_group_evaluate.m ├── cnn_save_model.m ├── cnn_softmax_evaluate.m ├── cnn_update_net_group.m ├── demo_evaluate_saved_prediction_voc.m ├── demo_fuse_saved_prediction_voc.m ├── demo_predict_mscale_ade.m ├── demo_predict_mscale_cityscapes.m ├── demo_predict_mscale_nyud.m ├── demo_predict_mscale_pascalcontext.m ├── demo_predict_mscale_person_parts.m ├── demo_predict_mscale_sunrgbd.m ├── demo_predict_mscale_voc.m ├── demo_refinenet_train.m ├── demo_refinenet_train_reduce_learning_rate.m ├── demo_test_simple_city.m ├── demo_test_simple_voc.m ├── disp_evaluate_result.m ├── evaluate_predict_results.m ├── fuse_multiscale_results.m ├── gen_class_info_ade.m ├── gen_class_info_cityscapes.m ├── gen_class_info_nyud.m ├── gen_class_info_pascalcontext.m ├── gen_class_info_person_parts.m ├── gen_class_info_sunrgbd.m ├── gen_class_info_voc.m ├── gen_dataset_info.m ├── gen_net_opts_model_type1.m ├── gen_net_opts_model_type2.m ├── gen_net_run_opts_basic.m ├── gen_network_featnet_imgraw.m ├── gen_network_featnet_resnet.m ├── gen_network_loss_group.m ├── gen_network_main.m ├── gen_network_pool_block.m ├── gen_network_refine_group.m ├── gen_padding_keep_size.m ├── get_current_work_group_idx.m ├── init_model_from_cache.m ├── load_img_from_ds_info.m ├── load_mask_from_ds_info.m ├── move_output_info_cpu.m ├── move_output_info_gpu.m ├── move_to_cpu_values.m ├── move_to_gpu_values.m ├── my_any.m ├── my_batch_run_config.m ├── my_clear_net_trn.m ├── my_epoch_model_cache.m ├── my_epoch_run_config.m ├── my_gen_ds_info_cityscapes.m ├── my_gen_ds_info_voc.m ├── my_gen_imdb.m ├── my_gen_seg_result.m ├── my_get_batch_ds_info.m ├── my_init_input_info.m ├── my_load_legacy_model.m ├── my_logsoftmax.m ├── my_matconvnet_resnet │ ├── +dagnn │ │ ├── BatchNorm.m │ │ └── BatchNorm_bak.m │ ├── @DagNN │ │ ├── DagNN.m │ │ ├── addLayer.m │ │ ├── do_backward_trn.m │ │ └── do_forward_trn.m │ ├── README.md │ └── impl │ │ ├── bnorm_cpu.cpp │ │ └── bnorm_gpu.cu ├── my_matlab.sh ├── my_matlab_nodisp.sh ├── my_move_net.m ├── my_net_backward.m ├── my_net_forward.m ├── my_net_progress_disp.m ├── my_net_run_batch.m ├── my_net_run_epoch.m ├── my_net_tool.m ├── my_resize.m ├── my_softmax.m ├── my_utils │ ├── README.txt │ ├── get_sub_dir_names.m │ ├── get_sub_file_names.m │ ├── make_ref_obj.m │ ├── mkdir_notexist.m │ ├── my_cell2mat.m │ ├── my_check_file.m │ ├── my_check_valid_numeric.m │ ├── my_diary_flush.m │ ├── my_gen_array_str.m │ ├── my_imshow.m │ ├── my_label_count.m │ ├── my_list_dir.m │ ├── my_list_file.m │ ├── my_load_file.m │ ├── my_random_sample.m │ ├── my_randperm.m │ ├── my_save_file.m │ ├── my_save_image.m │ ├── read_img_rgb.m │ └── ref_obj.m ├── pascalcontext_class_names.mat ├── prepare_runner_test_simple.m ├── prepare_running_model.m ├── process_class_info.m ├── process_ds_info_classification.m ├── process_ds_info_regression.m ├── seg_eva_gen_result_from_con_mat.m ├── seg_eva_one_img.m ├── sunrgbd_class_names.mat ├── update_eva_param_mscale.m ├── update_eva_result_batch.m └── 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