CVPR 2022 | Structured Sparse R-CNN:单阶段端到端场景图生成器 本文介绍我们在场景图生成 (Scene Graph Generation, SGG) 领域的工作——Structured Sparse R-CNN for Direct Scene Graph Generation。本工作将端到端稀疏目标检测器引入场景图生成领域,并提出了相应的关系建模组件和训练策略。该模型在 Visual Genom...
CVPR 2022 | Structured Sparse R-CNN:单阶段端到端场景图生成器 本文介绍我们在场景图生成 (Scene Graph Generation, SGG) 领域的工作——Structured Sparse R-CNN for Direct Scene Graph Generation。本工作将端到端稀疏目标检测器引入场景图生成领域,并提出了相应的关系建模组件和训练策略。该模型在 Visual Genom...
本文介绍我们在场景图生成 (Scene Graph Generation, SGG) 领域的工作——Structured Sparse R-CNN for Direct Scene Graph Generation。本工作将端到端稀疏目标检测器引入场景图生成领域,并提出了相应的关系建模组件和训练策略。该模型在 Visual Genome, Open Image V4/V6 数据集上取得了 SOTA 效果。论文和代码及模...
(2018) Weakly supervised action localization by sparse temporal pooling network. In The IEEE conference on computer vision and pattern recognition (CVPR) (pp. 6752–6761). Niebles, J. C., Chen, C. W., & Fei-Fei, L. (2010). Modeling temporal structure of decomposable motion segments for ...
CNN to predict disparities and textures for all LDI layers, we find it critical to have disjoint prediction branches to infer each LDI layer. We hypothesize that this occurs because the foreground layer gets more learning signal, and sharing all the prediction weights makes it difficult for the ...
(2) For low abundant antigens, signal is sparse and pixelated. Therefore, there is more information about positive signal in the density of positive pixels, rather than their intensity. To filter noise by signal density a k-nearest-neighbor approach was used. Each count was given a density-...
BioSR whose signal level ranging from 1 to 4 (MTs and CCPs) or 1 to 3 (ER). The average effective photon counts of these samples are 10 to 30-fold less than those used in artifact-free GT-SIM images. We compared PRS-SIM with conventional SIM (conv. SIM) and sparse-deconvolution ...
Network pruning is one of the methods which can lower the computational and memory requirements of CNNs. It generates a sparse network by removing redundant weights or activations through iterative training [2, 4, 5, 10, 14–16]. The early pruning methods focus on unstructured pruning, which ...
Hessian-SIM and proposed a Sparse-SIM deconvolution algorithm, which can achieve a resolution of ~60 nm at a frame rate of up to 564 fps. This method also enables four-color, 3D live-cell superresolution imaging at ~90 nm resolution. However, the resolution enhancement of Sparse-S...
extension: Same as GPT-2 with the only addition of alternating dense and locally banded sparse attention patterns, inspired by the Sparse Transformer application: Initially text generation, but has over time been used for a large range of applications in areas such as code generation, but also ...