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Found 3 papers, 3 papers with code
HuPR: A Benchmark for Human Pose Estimation Using Millimeter Wave Radar
In addition to the benchmark, we propose a cross-modality training framework that leverages the ground-truth 2D keypoints representing human body joints for training, which are systematically generated from the pre-trained 2D pose estimation network based on a monocular camera input image, avoiding laborious manual label annotation efforts.
Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional Networks
One common approach to this task is to propagate the activation scores of Class Activation Maps (CAMs) using a random-walk mechanism in order to arrive at complete pseudo labels for training a semantic segmentation network in a fully-supervised manner.
GSVNet: Guided Spatially-Varying Convolution for Fast Semantic Segmentation on Video
Moreover, we introduce a guided spatially-varying convolution for fusing segmentations derived from the previous and current frames, to mitigate propagation error and enable lightweight feature extraction on non-keyframes.
