Learning Rich Representations For Structured Visual Prediction Tasks | Paper Citation Record

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This paper cites Shotton, J.

Learning Rich Representations For Structured Visual Prediction Tasks Shotton, J

Reference 2

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This paper cites Efﬁcient inference in fully connected crfs with gaussian edge potentials.

Learning Rich Representations For Structured Visual Prediction Tasks Efﬁcient inference in fully connected crfs with gaussian edge potentials

Reference 3

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This paper cites Ladick`y, C.

Learning Rich Representations For Structured Visual Prediction Tasks Ladick`y, C

Reference 4

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This paper cites Pylon model for semantic segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Pylon model for semantic segmentation

Reference 5

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This paper cites Discriminative re-ranking of diverse segmentations.

Learning Rich Representations For Structured Visual Prediction Tasks Discriminative re-ranking of diverse segmentations

Reference 6

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This paper cites Diverse M-Best Solutions in Markov Random Fields.

Learning Rich Representations For Structured Visual Prediction Tasks Diverse M-Best Solutions in Markov Random Fields

Reference 7

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This paper cites Gonfaus, Joost van de Weijer, Andrew D.

Learning Rich Representations For Structured Visual Prediction Tasks Gonfaus, Joost van de Weijer, Andrew D

Reference 8

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This paper cites A robust multilevel segment de- scription for multi-class object recognition.

Learning Rich Representations For Structured Visual Prediction Tasks A robust multilevel segment de- scription for multi-class object recognition

Reference 9

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This paper cites Kolkin, and Gregory Shakhnarovich.

Learning Rich Representations For Structured Visual Prediction Tasks Kolkin, and Gregory Shakhnarovich

Reference 10

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This paper cites ImageNet: A large-scale hierarchical image database.

Learning Rich Representations For Structured Visual Prediction Tasks ImageNet: A large-scale hierarchical image database

Reference 11

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This paper cites Semantic image segmentation via deep parsing network.

Learning Rich Representations For Structured Visual Prediction Tasks Semantic image segmentation via deep parsing network

Reference 12

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This paper cites Pyramid scene parsing network.

Learning Rich Representations For Structured Visual Prediction Tasks Pyramid scene parsing network

Reference 14

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This paper cites The PASCAL Visual Object Classes (VOC) challenge.

Learning Rich Representations For Structured Visual Prediction Tasks The PASCAL Visual Object Classes (VOC) challenge

Reference 15

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This paper cites Lawrence Zitnick.

Learning Rich Representations For Structured Visual Prediction Tasks Lawrence Zitnick

Reference 16

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This paper cites Regularizing 109 deep networks by modeling and predicting label structure.

Learning Rich Representations For Structured Visual Prediction Tasks Regularizing 109 deep networks by modeling and predicting label structure

Reference 17

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This paper cites Arbelaez, M.

Learning Rich Representations For Structured Visual Prediction Tasks Arbelaez, M

Reference 18

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This paper cites Martin, C.

Learning Rich Representations For Structured Visual Prediction Tasks Martin, C

Reference 19

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This paper cites Slic superpixels compared to state-of-the-art superpixel methods.

Learning Rich Representations For Structured Visual Prediction Tasks Slic superpixels compared to state-of-the-art superpixel methods

Reference 20

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This paper cites Comaniciu and P.

Learning Rich Representations For Structured Visual Prediction Tasks Comaniciu and P

Reference 21

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This paper cites Carreira and C.

Learning Rich Representations For Structured Visual Prediction Tasks Carreira and C

Reference 22

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This paper cites Normalized cuts and image segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Normalized cuts and image segmentation

Reference 23

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

Reference 24

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This paper cites W-Net: A Deep Model for Fully Unsupervised Image Segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks W-Net: A Deep Model for Fully Unsupervised Image Segmentation

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Learning Rich Representations For Structured Visual Prediction Tasks Panoptic Segmentation

Reference 26

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This paper cites Cpmc: Automatic object segmentation using constrained parametric min-cuts.

Learning Rich Representations For Structured Visual Prediction Tasks Cpmc: Automatic object segmentation using constrained parametric min-cuts

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

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Learning Rich Representations For Structured Visual Prediction Tasks Arbelaez, B

Reference 29

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Learning Rich Representations For Structured Visual Prediction Tasks Semantic segmentation with second-order pooling

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Learning Rich Representations For Structured Visual Prediction Tasks Probabilistic joint image segmentation and labeling

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Learning Rich Representations For Structured Visual Prediction Tasks Object recognition by sequential ﬁgure-ground ranking

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

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Learning Rich Representations For Structured Visual Prediction Tasks Simultaneous detection and segmentation

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This paper cites Combining the Best of Graphical Models and ConvNets for Semantic Segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Combining the Best of Graphical Models and ConvNets for Semantic Segmentation

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Learning Rich Representations For Structured Visual Prediction Tasks Class segmentation and object localization with superpixel neighborhoods

Reference 36

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Learning Rich Representations For Structured Visual Prediction Tasks Context by region ancestry

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Learning Rich Representations For Structured Visual Prediction Tasks Are spatial and global constraints really necessary for segmentation? In ICCV, 2011

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Learning Rich Representations For Structured Visual Prediction Tasks Learning hierarchical features for scene labeling

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

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Learning Rich Representations For Structured Visual Prediction Tasks Lin, Andrew Y

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Learning Rich Representations For Structured Visual Prediction Tasks Deep and Wide Multiscale Recursive Networks for Robust Image Labeling

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Learning Rich Representations For Structured Visual Prediction Tasks Fully convolutional networks for semantic segmentation

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Learning Rich Representations For Structured Visual Prediction Tasks Hypercolumns for object segmentation and ﬁne-grained localization

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Learning Rich Representations For Structured Visual Prediction Tasks Slic superpixels compared to state-of-the-art superpixel methods

Reference 45

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Learning Rich Representations For Structured Visual Prediction Tasks Williams, John Winn, and Andrew Zisserman

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Learning Rich Representations For Structured Visual Prediction Tasks ImageNet Large Scale Visual Recognition Challenge

Reference 47

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Learning Rich Representations For Structured Visual Prediction Tasks Structured output learning with high order loss functions

Reference 48

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Learning Rich Representations For Structured Visual Prediction Tasks Segmentation propagation in imagenet

Reference 49

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Learning Rich Representations For Structured Visual Prediction Tasks Semantic contours from inverse detectors

Reference 50

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Learning Rich Representations For Structured Visual Prediction Tasks Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

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Learning Rich Representations For Structured Visual Prediction Tasks Chatﬁeld, K

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Learning Rich Representations For Structured Visual Prediction Tasks Simonyan and A

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Learning Rich Representations For Structured Visual Prediction Tasks Girshick, J

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Learning Rich Representations For Structured Visual Prediction Tasks Deep residual learning for image recognition

Reference 56

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Learning Rich Representations For Structured Visual Prediction Tasks Weinberger

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Learning Rich Representations For Structured Visual Prediction Tasks Learning Transferable Architectures for Scalable Image Recognition

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Learning Rich Representations For Structured Visual Prediction Tasks Caffe: Convolutional architecture for fast feature embedding

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Learning Rich Representations For Structured Visual Prediction Tasks Srivastava, G

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

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Learning Rich Representations For Structured Visual Prediction Tasks Hariharan, P

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Learning Rich Representations For Structured Visual Prediction Tasks Imagenet classiﬁcation with deep convolutional neural networks

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Learning Rich Representations For Structured Visual Prediction Tasks https://github.com/pytorch/pytorch

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Learning Rich Representations For Structured Visual Prediction Tasks Kingma and Jimmy Ba

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Learning Rich Representations For Structured Visual Prediction Tasks https://github.com/pytorch/vision

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Learning Rich Representations For Structured Visual Prediction Tasks Multi-scale context aggregation by dilated convolutions

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This paper cites DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

Learning Rich Representations For Structured Visual Prediction Tasks DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Reference 68

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Observation 82b0679d-d164-4b26-bccf-8d6e1eb62770 · outbound

This paper cites Holschneider, R.

Learning Rich Representations For Structured Visual Prediction Tasks Holschneider, R

Reference 69

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Observation c236d0b3-cec6-49d7-b4a7-398d17e3d314 · outbound

This paper cites Semantic understanding of scenes through the ade20k dataset.

Learning Rich Representations For Structured Visual Prediction Tasks Semantic understanding of scenes through the ade20k dataset

Reference 70

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Observation 6a169a50-ac62-43f7-ba84-91e67bf3f585 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 71

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Learning Rich Representations For Structured Visual Prediction Tasks Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 72

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Learning Rich Representations For Structured Visual Prediction Tasks Multi-scale context intertwining for semantic segmentation

Reference 73

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Observation 5bbb5b69-91e1-4245-8902-06be1217ab98 · outbound

This paper cites Cordts, M.

Learning Rich Representations For Structured Visual Prediction Tasks Cordts, M

Reference 74

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This paper cites Torchcv: A pytorch-based framework for deep learning in computer vision.

Learning Rich Representations For Structured Visual Prediction Tasks Torchcv: A pytorch-based framework for deep learning in computer vision

Reference 75

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

Reference 76

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This paper cites Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, Evrim B.

Learning Rich Representations For Structured Visual Prediction Tasks Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, Evrim B

Reference 77

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Observation 014b80e4-8ced-4b69-bce4-9f9d5540acc3 · outbound

This paper cites Roth, Jiamin Liu, Evrim Turkbey, and Ronald M.

Learning Rich Representations For Structured Visual Prediction Tasks Roth, Jiamin Liu, Evrim Turkbey, and Ronald M

Reference 78

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Learning Rich Representations For Structured Visual Prediction Tasks Training deep networks to be spatially sensitive

Reference 79

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Learning Rich Representations For Structured Visual Prediction Tasks Shimoda and K

Reference 80

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Learning Rich Representations For Structured Visual Prediction Tasks Learning representations for automatic colorization

Reference 81

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

Reference 82

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Learning Rich Representations For Structured Visual Prediction Tasks Unresolved cited work

Reference 83

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Learning Rich Representations For Structured Visual Prediction Tasks Learning deep features for scene recognition using places database

Reference 84

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Observation 35500db6-100f-4cfb-a3af-2b23a7e21536 · outbound

This paper cites The pascal visual object classes challenge: A retrospective.

Learning Rich Representations For Structured Visual Prediction Tasks The pascal visual object classes challenge: A retrospective

Reference 85

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Observation a0774d1b-960b-4007-866a-ec4ee52db6af · outbound

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Learning Rich Representations For Structured Visual Prediction Tasks Microsoft coco: Common objects in context

Reference 86

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Learning Rich Representations For Structured Visual Prediction Tasks Object detectors emerge in deep scene cnns

Reference 87

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This paper cites Is object localization for free?-weakly-supervised learning with convolutional neural networks.

Learning Rich Representations For Structured Visual Prediction Tasks Is object localization for free?-weakly-supervised learning with convolutional neural networks

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.194799Z

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Observation 23aa3bae-6009-4a27-a7dc-1ac484460059 · outbound

This paper cites What's the Point: Semantic Segmentation with Point Supervision.

Learning Rich Representations For Structured Visual Prediction Tasks What's the Point: Semantic Segmentation with Point Supervision

Reference 89

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Learning Rich Representations For Structured Visual Prediction Tasks Hariharan, P

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.176764Z

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Observation ba11bf6d-f27d-49a2-9b14-9e9830bdfec1 · outbound

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Learning Rich Representations For Structured Visual Prediction Tasks Mostajabi, P

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.160880Z

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Observation 82ca1cb7-016c-4fcd-a856-19b2f2617b99 · outbound

This paper cites Weakly- and semi-supervised learning of a deep convolutional network for semantic image segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Weakly- and semi-supervised learning of a deep convolutional network for semantic image segmentation

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.144971Z

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Observation 28d4a5bb-5eea-4fca-a6f2-cab82aea7dc4 · outbound

This paper cites Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-14T10:12:09.359245Z

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This paper cites Simple Does It: Weakly Supervised Instance and Semantic Segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Simple Does It: Weakly Supervised Instance and Semantic Segmentation

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-14T10:12:09.365161Z

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Learning Rich Representations For Structured Visual Prediction Tasks Constrained convolutional neural networks for weakly supervised segmentation

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.117331Z

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Observation d9ba377a-b2a3-47a7-8e68-34281d006429 · outbound

This paper cites Self-taught Object Localization with Deep Networks.

Learning Rich Representations For Structured Visual Prediction Tasks Self-taught Object Localization with Deep Networks

Reference 96

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:12:09.788599Z

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Observation e83827fb-084a-4689-8012-1a5265da0445 · outbound

This paper cites Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning.

Learning Rich Representations For Structured Visual Prediction Tasks Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning

Reference 97

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:12:09.765096Z

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Observation 334b5d27-c0be-45a3-b558-662e46240b46 · outbound

This paper cites Schwing, and Raquel Urtasun.

Learning Rich Representations For Structured Visual Prediction Tasks Schwing, and Raquel Urtasun

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.100288Z

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Observation a08c45ea-66f3-47f0-8ae3-38402f241d5c · outbound

This paper cites Fully convolu- tional multi-class multiple instance learning.

Learning Rich Representations For Structured Visual Prediction Tasks Fully convolu- tional multi-class multiple instance learning

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.084467Z

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Observation 946ceaef-1d46-4655-93db-df146aad35ab · outbound

This paper cites From image-level to pixel-level labeling with convolutional networks.

Learning Rich Representations For Structured Visual Prediction Tasks From image-level to pixel-level labeling with convolutional networks

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:12:11.068784Z

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Observation eaf4e4bc-5f77-420d-aa8d-9f4080b25e26 · outbound

This paper cites Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation.

Learning Rich Representations For Structured Visual Prediction Tasks Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation

Reference 101

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