Residual layer with multi grids

Cascade of 2D convolution, batch norm, and ReLU.

Residual layer with multi grids

Multi-scale inputs

Cascade of 2D convolution, batch norm, and ReLU.

The 1st conv layer. Note that the max pooling is different from both MSRA and FAIR ResNet.

DeepLab v2: Dilated ResNet + ASPP Output stride is fixed at 8

ResNet Variants Parameters ---------- block : Block Class for the residual block. Options are BasicBlockV1, BottleneckV1. lay

based on threshold

DeepLab v1: Dilated ResNet + 1x1 Conv Note that this is just a container for loading the pretrained COCO model and not mentioned as "v1" in p

DeepLab v2: Dilated ResNet + ASPP Output stride is fixed at 8

DeepLab v3: Dilated ResNet with multi-grid + improved ASPP

DeepLab v3+: Dilated ResNet with multi-grid + improved ASPP + decoder

Atrous spatial pyramid pooling (ASPP)

The 1st conv layer. Note that the max pooling is different from both MSRA and FAIR ResNet.

COCO-Stuff 164k dataset

A thread-safe future implementation. Used only as one-to-one pipe.

Multi-scale inputs

Pipe for master-slave communication.

Split-Attention Conv2d

An abstract `SyncMaster` object. - During the replication, as the data parallel will trigger an callback of each module, all slave devices should

PASCAL VOC Segmentation dataset with extra annotations

Atrous spatial pyramid pooling (ASPP)

Atrous spatial pyramid pooling with image-level feature

Bottleneck block of MSRA ResNet.

Bottleneck block of MSRA ResNet.

ResNet Bottleneck