Fetching the paper…
Reading the bibliography…
We present a box-free bottom-up approach for the tasks of pose estimation and instance segmentation of people in multi-person images using an efficient single-shot model.
The representation and matching of pictorial structures
Fischler, M.A., Elschlager, R.: · 1973
Earlier work this paper cites.
Gradient-based learning applied to document recognition
LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: · 1998
Earlier work this paper cites.
A discriminatively trained, multiscale, deformable part model
Felzenszwalb, P., McAllester, D., Ramanan, D.: · 2008
Earlier work this paper cites.
Pictorial structures revisited: People detection and articulated pose estimation
Andriluka, M., Roth, S., Schiele, B.: · 2009
Earlier work this paper cites.
Better appearance models for pictorial structures
Eichner, M., Ferrari, V.: · 2009
Earlier work this paper cites.
Adaptive pose priors for pictorial structures
Sapp, B., Jordan, C., B.Taskar: · 2010
Earlier work this paper cites.
Articulated pose estimation with flexible mixtures of parts
Yang, Y., Ramanan, D.: · 2011
Earlier work this paper cites.
Learning Effective Human Pose Estimation from Inaccurate Annotation
Johnson, S., Everingham, M.: · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
Earlier work this paper cites.
CPMC: Automatic object segmentation using constrained parametric min-cuts
Carreira, J., Sminchisescu, C.: · 2012
Earlier work this paper cites.
Human pose estimation using body parts dependent joint regressors
Dantone, M., Gall, J., Leistner, C., Gool., L.V.: · 2013
Earlier work this paper cites.
Poselet conditioned pictorial structures
Pishchulin, L., Andriluka, M., Gehler, P., Schiele, B.: · 2013
Earlier work this paper cites.
Modec: Multimodal decomposable models for human pose estimation
Sapp, B., Taskar, B.: · 2013
Earlier work this paper cites.
Articulated pose estimation using discriminative armlet classifiers
Gkioxari, G., Arbelaez, P., Bourdev, L., Malik, J.: · 2013
Earlier work this paper cites.
Deeppose: Human pose estimation via deep neural networks
Toshev, A., Szegedy, C.: · 2014
Earlier work this paper cites.
Learning human pose estimation features with convolutional networks
Jain, A., Tompson, J., Andriluka, M., Taylor, G., Bregler, C.: · 2014
Earlier work this paper cites.
Join training of a convolutional network and a graphical model for human pose estimation
Tompson, J., Jain, A., LeCun, Y., Bregler, C.: · 2014
Earlier work this paper cites.
Articulated pose estimation by a graphical model with image dependent pairwise relations
Chen, X., Yuille, A.: · 2014
Earlier work this paper cites.
2d human pose estimation: New benchmark and state of the art analysis
Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.: · 2014
Earlier work this paper cites.
Multiscale combinatorial grouping
Arbeláez, P., Pont-Tuset, J., Barron, J.T., Marques, F., Malik, J.: · 2014
Earlier work this paper cites.
Simultaneous detection and segmentation
Hariharan, B., Arbeláez, P., Girshick, R., Malik, J.: · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: · 2014
Earlier work this paper cites.
Efficient object localization using convolutional networks
Tompson, J., Goroshin, R., Jain, A., LeCun, Y., Bregler, C.: · 2015
Earlier work this paper cites.
Fast r-cnn
Girshick, R.: · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Ren, S., He, K., Girshick, R., Sun, J.: · 2015
Earlier work this paper cites.
Learning to segment object candidates
Pinheiro, P.O., Collobert, R., Dollár, P.: · 2015
Cited alongside, same era.
Convolutional feature masking for joint object and stuff segmentation
Dai, J., He, K., Sun, J.: · 2015
Cited alongside, same era.
Proposal-free network for instance-level object segmentation
Liang, X., Wei, Y., Shen, X., Yang, J., Lin, L., Yan, S.: · 2015
Cited alongside, same era.
Monocular object instance segmentation and depth ordering with cnns
Zhang, Z., Schwing, A.G., Fidler, S., Urtasun, R.: · 2015
Cited alongside, same era.
Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., Darrell, T.: · 2015
Cited alongside, same era.
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: · 2015
Bridging category-level and instance-level semantic image segmentation
Wu, Z., Shen, C., van den Hengel, A.: · 2016
Later among the works it cites.
Multi-scale patch aggregation (mpa) for simultaneous detection and segmentation
Liu, S., Qi, X., Shi, J., Zhang, H., Jia, J.: · 2016
Later among the works it cites.
Object detection free instance segmentation with labeling transformations
Jin, L., Chen, Z., Tu, Z.: · 2016
Later among the works it cites.
Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., Sun, J.: · 2016
Later among the works it cites.
Associative embedding: End-to-end learning for joint detection and grouping
Newell, A., Deng, J.: · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, S., Szegedy, C.: · 2015
Cited alongside, same era.
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., et al.: · 2015
Cited alongside, same era.
Coco 2016 keypoint challenge
Lin, T.Y., Cui, Y., Patterson, G., Ronchi, M.R., Bourdev, L., Girshick, R., Dollár, P.: · 2016
Cited alongside, same era.
Stacked hourglass networks for human pose estimation
Newell, A., Yang, K., Deng, J.: · 2016
Cited alongside, same era.
Human pose estimation via convolutional part heatmap regression
Bulat, A., Tzimiropoulos, G.: · 2016
Cited alongside, same era.
Recurrent human pose estimation
Belagiannis, V., Zisserman, A.: · 2016
Cited alongside, same era.
Fully convolutional instance-aware semantic segmentation
Li, Y., Qi, H., Dai, J., Ji, X., Wei, Y.: · 2017
Later among the works it cites.
Realtime multi-person 2d pose estimation using part affinity fields
Cao, Z., Simon, T., Wei, S.E., Sheikh, Y.: · 2017
Later among the works it cites.
Towards accurate multi-person pose estimation in the wild
Papandreou, G., Zhu, T., Kanazawa, N., Toshev, A., Tompson, J., Bregler, C., Murphy, K.: · 2017
Later among the works it cites.
He, K., Gkioxari, G., Dollár, P., Girshick, R.: · 2017
Later among the works it cites.
A coarse-fine network for keypoint localization
Huang, S., Gong, M., Tao, D.: · 2017
Later among the works it cites.
RMPE: Regional multi-person pose estimation
Fang, H.S., Xie, S., Tai, Y.W., Lu, C.: · 2017
Later among the works it cites.
Cascaded pyramid network for multi-person pose estimation
Chen, Y., Wang, Z., Peng, Y., Zhang, Z., Yu, G., Sun, J.: · 2017
Later among the works it cites.
Joint graph decomposition & node labeling: Problem, algorithms, applications
Levinkov, E., Uhrig, J., Tang, S., Omran, M., Insafutdinov, E., Kirillov, A., Rother, C., Brox, T., Schiele, B., Andres, B.: · 2017
Later among the works it cites.
Instancecut: from edges to instances with multicut
Kirillov, A., Levinkov, E., Andres, B., Savchynskyy, B., Rother, C.: · 2017
Later among the works it cites.
Semantic instance segmentation via deep metric learning
Fathi, A., Wojna, Z., Rathod, V., Wang, P., Song, H.O., Guadarrama, S., Murphy, K.P.: · 2017
Later among the works it cites.
Semantic instance segmentation with a discriminative loss function
De Brabandere, B., Neven, D., Van Gool, L.: · 2017
Later among the works it cites.
Deep watershed transform for instance segmentation
Bai, M., Urtasun, R.: · 2017
Later among the works it cites.
Sgn: Sequential grouping networks for instance segmentation
Liu, S., Jia†, J., Fidler, S., Urtasun, R.: · 2017
Later among the works it cites.
Soft-nms: Improving object detection with one line of code
Bodla, N., Singh, B., Chellappa, R., Davis, L.S.: · 2017
Later among the works it cites.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: · 2017
Later among the works it cites.
Data distillation: Towards omni-supervised learning
Radosavovic, I., Dollár, P., Girshick, R., Gkioxari, G., He, K.: · 2017
Later among the works it cites.
Megdet: A large mini-batch object detector
Peng, C., Xiao, T., Li, Z., Jiang, Y., Zhang, X., Jia, K., Yu, G., Sun, J.: · 2018
Closest in time.
Masklab: Instance segmentation by refining object detection with semantic and direction features
Chen, L.C., Hermans, A., Papandreou, G., Schroff, F., Wang, P., Adam, H.: · 2018
Closest in time.
Path aggregation network for instance segmentation
Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.: · 2018
Closest in time.