Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation | Paper Citation Record

Observation 02682b69-4ee3-46db-b899-ddd35da1c820 · outbound

This paper cites Learning pixel-level semantic afﬁnity with image-level supervision for weakly supervised semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Learning pixel-level semantic afﬁnity with image-level supervision for weakly supervised semantic segmentation

Reference 1

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Observation be9c6428-d5b8-4d7a-9ae0-9cf1fcf5faf7 · outbound

This paper cites Discovering class-speciﬁc pixels for weakly-supervised se- mantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Discovering class-speciﬁc pixels for weakly-supervised se- mantic segmentation

Reference 2

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Observation 91ed2ef5-5fc2-43b2-8d9c-eac63060f428 · outbound

This paper cites Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Reference 3

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Observation ab70b850-f1bb-4f1c-8c56-b84a037268ae · outbound

This paper cites Boxsup: Exploit- ing bounding boxes to supervise convolutional networks for semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Boxsup: Exploit- ing bounding boxes to supervise convolutional networks for semantic segmentation

Reference 4

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Observation 8c08bf40-6dd0-4f00-a396-fd77d8510762 · outbound

This paper cites Imagenet: A large-scale hierarchical im- age database.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Imagenet: A large-scale hierarchical im- age database

Reference 5

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Observation 082b6d0a-c83e-45cb-88b0-ee9c02223b9c · outbound

This paper cites Object Detection, Tracking, and Motion Segmentation for Object-level Video Segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Object Detection, Tracking, and Motion Segmentation for Object-level Video Segmentation

Reference 6

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Observation fec44846-5bac-4ecc-83c8-0aafc252efe5 · outbound

This paper cites The pascal visual object classes (voc) challenge.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation The pascal visual object classes (voc) challenge

Reference 7

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Observation 478c92ac-29a5-4497-86e1-775dc64968b6 · outbound

This paper cites CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation

Reference 8

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Observation 47b74f09-bbaa-4222-a399-c2b4f0c741c8 · outbound

This paper cites Multi-evidence ﬁltering and fusion for multi-label classiﬁcation, object de- tection and semantic segmentation based on weakly super- vised learning.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Multi-evidence ﬁltering and fusion for multi-label classiﬁcation, object de- tection and semantic segmentation based on weakly super- vised learning

Reference 9

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Observation 62788e14-4da8-48e3-a328-0d98e6747e46 · outbound

This paper cites Deep residual learning for image recognition.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Deep residual learning for image recognition

Reference 10

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Observation 33cc27a4-abb8-47cf-8ba6-24be304b749f · outbound

This paper cites Learning transferrable knowledge for semantic seg- mentation with deep convolutional neural network.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Learning transferrable knowledge for semantic seg- mentation with deep convolutional neural network

Reference 11

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Observation 32d4bbd7-efe8-4aed-91e3-3ef1d5cd30d1 · outbound

This paper cites Weakly supervised semantic segmenta- tion using web-crawled videos.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Weakly supervised semantic segmenta- tion using web-crawled videos

Reference 12

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Observation dbf2c948-a0fd-4304-b841-b02160e76ed9 · outbound

This paper cites Deeply supervised salient object detection with short connections.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Deeply supervised salient object detection with short connections

Reference 13

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Observation 12eb8ed2-718c-473b-a123-dc646700bdfd · outbound

This paper cites WebSeg: Learning Semantic Segmentation from Web Searches.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation WebSeg: Learning Semantic Segmentation from Web Searches

Reference 14

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Observation 05989b2c-a57f-4faf-aa2d-9f044f64bf97 · outbound

This paper cites Self-erasing network for integral object attention.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Self-erasing network for integral object attention

Reference 15

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Observation 718ae4f2-08af-4c86-bff2-0ba54f626aea · outbound

This paper cites Associating inter-image salient instances for weakly supervised semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Associating inter-image salient instances for weakly supervised semantic segmentation

Reference 16

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Observation b1d04a0a-2df5-4734-a19f-e231d70a24a4 · outbound

This paper cites Weakly-supervised semantic segmentation network with deep seeded region growing.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Weakly-supervised semantic segmentation network with deep seeded region growing

Reference 17

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Observation 95f54f61-3eca-49eb-b7a9-576a161320aa · outbound

This paper cites Supervoxel- consistent foreground propagation in video.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Supervoxel- consistent foreground propagation in video

Reference 18

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Observation 1d33efd4-9c6d-47d5-8c7b-b81d2956ef38 · outbound

This paper cites Primary object segmentation in videos via alternate convex optimiza- tion of foreground and background distributions.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Primary object segmentation in videos via alternate convex optimiza- tion of foreground and background distributions

Reference 19

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Observation 6b97cd84-f490-4fb5-98be-634cc9beb439 · outbound

This paper cites Caffe: Convolutional architecture for fast feature embedding.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Caffe: Convolutional architecture for fast feature embedding

Reference 20

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Observation 5cffc7f8-f57f-4a17-95ed-8565aae36622 · outbound

This paper cites We- bly supervised semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation We- bly supervised semantic segmentation

Reference 21

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Observation ee578fd5-5dab-42a8-8bcc-03892fedfe80 · outbound

This paper cites Two-phase learning for weakly supervised object localization.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Two-phase learning for weakly supervised object localization

Reference 22

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Observation 35c2e2f5-1964-4abc-a136-e97dd4eb033b · outbound

This paper cites Seed, ex- pand and constrain: Three principles for weakly-supervised image segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Seed, ex- pand and constrain: Three principles for weakly-supervised image segmentation

Reference 23

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Observation eed1a8c1-be6f-4fe5-bfe3-0f5d1b3411d5 · outbound

This paper cites Ficklenet: Weakly and semi-supervised se- mantic image segmentation using stochastic inference.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Ficklenet: Weakly and semi-supervised se- mantic image segmentation using stochastic inference

Reference 24

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Observation f3d90260-649c-40ad-97e0-626ed8eabe5d · outbound

This paper cites Robust Tumor Localization with Pyramid Grad-CAM.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Robust Tumor Localization with Pyramid Grad-CAM

Reference 25

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Observation 1bbcec27-fa34-4e37-b24f-e38c55a2a64f · outbound

This paper cites Tell me where to look: Guided attention inference network.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Tell me where to look: Guided attention inference network

Reference 26

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Observation 46431c71-c144-4c72-8eee-c7d722bb5ec6 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Fully convolutional networks for semantic segmentation

Reference 27

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Observation 161c241c-f68d-47a9-b690-32a0fc2f9fa9 · outbound

This paper cites Fast object segmen- tation in unconstrained video.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Fast object segmen- tation in unconstrained video

Reference 28

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This paper cites Automatic dif- ferentiation in pytorch.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Automatic dif- ferentiation in pytorch

Reference 29

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Observation 1b260f41-9542-4fe1-bc11-9f0215711269 · outbound

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

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation From image-level to pixel-level labeling with convolutional networks

Reference 30

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Observation 65722d76-f668-4fb4-b173-874ed4b72c58 · outbound

This paper cites Learning object class detec- tors from weakly annotated video.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Learning object class detec- tors from weakly annotated video

Reference 31

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Observation f0e5c4ff-d8b8-4d28-a51b-52935d2e9378 · outbound

This paper cites Grabcut: Interactive foreground extraction using iterated graph cuts.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Grabcut: Interactive foreground extraction using iterated graph cuts

Reference 32

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This paper cites Combining bottom-up, top-down, and smoothness cues for weakly supervised im- age segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Combining bottom-up, top-down, and smoothness cues for weakly supervised im- age segmentation

Reference 33

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This paper cites Bringing background into the foreground: Making all classes equal in weakly-supervised video semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Bringing background into the foreground: Making all classes equal in weakly-supervised video semantic segmentation

Reference 34

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Observation e483c11c-21cc-4278-8ddd-70facf9dacd3 · outbound

This paper cites Bootstrapping the performance of webly supervised seman- tic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Bootstrapping the performance of webly supervised seman- tic segmentation

Reference 35

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Observation 53142c9e-385c-4817-a6a0-b650644eedec · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 36

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This paper cites Dropout: a simple way to prevent neural networks from overﬁtting.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Dropout: a simple way to prevent neural networks from overﬁtting

Reference 37

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Observation c7093700-1c7d-41a4-b6c5-ac8d72163d20 · outbound

This paper cites Pwc-net: Cnns for optical ﬂow using pyramid, warping, and cost volume.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Pwc-net: Cnns for optical ﬂow using pyramid, warping, and cost volume

Reference 38

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Observation 1d153998-306c-4dd7-884d-28bc752e154e · outbound

This paper cites Discriminative segment annotation in weakly labeled video.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Discriminative segment annotation in weakly labeled video

Reference 39

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Observation 927c4bce-723a-4291-9209-37559661f837 · outbound

This paper cites Normalized cut loss for weakly-supervised cnn segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Normalized cut loss for weakly-supervised cnn segmentation

Reference 40

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Observation 8446da94-f187-4ddf-9400-4a9efbae123b · outbound

This paper cites On regularized losses for weakly-supervised cnn segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation On regularized losses for weakly-supervised cnn segmentation

Reference 41

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Observation 3cf214e0-450c-41c0-b5a7-956cf73c2aeb · outbound

This paper cites Weakly-supervised semantic segmentation using motion cues.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Weakly-supervised semantic segmentation using motion cues

Reference 42

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Observation f6f16da1-ea6c-4dc4-a1a1-ffd4d695151d · outbound

This paper cites Weakly- supervised semantic segmentation by iteratively mining common object features.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Weakly- supervised semantic segmentation by iteratively mining common object features

Reference 43

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Observation 35486cdb-2031-4bd7-a0fb-16670e295e40 · outbound

This paper cites Object region mining with adversarial erasing: A simple classiﬁcation to semantic segmentation approach.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Object region mining with adversarial erasing: A simple classiﬁcation to semantic segmentation approach

Reference 44

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Observation 6d17bd0b-fe83-4b4b-9db9-adc13a091f41 · outbound

This paper cites Stc: A simple to complex framework for weakly- supervised semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Stc: A simple to complex framework for weakly- supervised semantic segmentation

Reference 45

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Observation bdc0198c-6973-4df6-bdb4-be01cf929e78 · outbound

This paper cites Revisiting dilated convolution: A simple approach for weakly-and semi-supervised seman- tic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Revisiting dilated convolution: A simple approach for weakly-and semi-supervised seman- tic segmentation

Reference 46

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Observation 224c5c40-f8d8-40e8-809b-3d2539c4f7ff · outbound

This paper cites Segmentation in weakly labeled videos via a seman- tic ranking and optical warping network.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Segmentation in weakly labeled videos via a seman- tic ranking and optical warping network

Reference 47

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Observation 9289716b-a981-473a-86bd-467aade28d6c · outbound

This paper cites Learning a discriminative feature network for semantic segmentation.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Learning a discriminative feature network for semantic segmentation

Reference 48

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Observation b8048280-2458-440a-af43-4e3a0287479e · outbound

This paper cites Adversarial complementary learning for weakly supervised object localization.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Adversarial complementary learning for weakly supervised object localization

Reference 49

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Observation 2fb351ab-ca85-40ae-9605-67f0a1a94719 · outbound

This paper cites Semantic object segmentation via detection in weakly labeled video.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Semantic object segmentation via detection in weakly labeled video

Reference 50

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This paper cites Semantic object segmentation in tagged videos via detection.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Semantic object segmentation in tagged videos via detection

Reference 51

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This paper cites Pyramid scene parsing network.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Pyramid scene parsing network

Reference 52

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This paper cites Learning deep features for discrimi- native localization.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation Learning deep features for discrimi- native localization

Reference 53

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Observation 0df2e2f3-c8a1-44b4-9739-a9941f27f019 · outbound

This paper cites IEEE Conference on , pages 248–255.

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation IEEE Conference on , pages 248–255

Reference 2009

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