We release a light and portable version of Network Dissection in pyTorch at NetDissect-Lite. It is much faster than this first version and the code structure is cleaned up, without any complex …

Network Dissection is our method for quantifying interpretability of individual units in a deep CNN (i.e., our answer to question #1). It works by measuring the alignment between unit response …

The BrodenHandle is a handle for datasets following the format of the Broad and Densely Labeled Dataset (Broden) dataset introduced in this paper. The original Broden dataset is not …

新数据集构建的基础是 Broadly Densely Labeled Dataset（Broden），这是一个包含不同视觉概念的混杂数据集。但是由于其设计初衷，Broden 并不适用于分割网络的训练。为此本文从 4 个 …

This is a pyTorch implementation of Unified Perceptual Parsing network on Broden+ dataset and ADE20K dataset. This work is published at ECCV'18 Unified Perceptual Parsing for Scene …

Handles for Broden-like datasets. The original Broad and Densely Labeled Dataset (Broden) was introduced in [Bau2017] as a combination of several existing semantic segmentation and …

作者首先建立了一个完善的测试数据集，叫做Broden（Broadly and Densely Labeled Dataset），每张图片都在场景、物体、材质、纹理、颜色等层面有pixel-wise的标定。 接下 …

2020年2月18日 · To identify a set of human-labeled visual concepts, the authors constructed the Broadly and Densely Labeled Dataset (Broden) dataset. The Broden dataset combines …

2018年11月26日 · Load the segmentation dataset using the BrodenDataset class; use the transform_image argument to normalize images to be suitable for the model, and the size …

2023年7月19日 · 作者建立了一个完善的测试数据集，叫做Broden（Broadly and Densely Labeled Dataset），每张图片都在场景、物体、材质、纹理、颜色等层面有pixel-wise的标定。 …