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09/14/2023
Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation
Modern approaches have proved the huge potential of addressing semantic ...
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07/22/2023
Edge Guided GANs with Multi-Scale Contrastive Learning for Semantic Image Synthesis
We propose a novel ECGAN for the challenging semantic image synthesis ta...
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05/17/2023
Object Segmentation by Mining Cross-Modal Semantics
Multi-sensor clues have shown promise for object segmentation, but inher...
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04/23/2023
Indiscernible Object Counting in Underwater Scenes
Recently, indiscernible scene understanding has attracted a lot of atten...
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07/21/2022
Mining Relations among Cross-Frame Affinities for Video Semantic Segmentation
The essence of video semantic segmentation (VSS) is how to leverage temp...
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04/07/2022
Coarse-to-Fine Feature Mining for Video Semantic Segmentation
The contextual information plays a core role in semantic segmentation. A...
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08/23/2021
SwinIR: Image Restoration Using Swin Transformer
Image restoration is a long-standing low-level vision problem that aims ...
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08/11/2021
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution
Existing blind image super-resolution (SR) methods mostly assume blur ke...
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08/04/2021
Boosting Few-shot Semantic Segmentation with Transformers
Due to the fact that fully supervised semantic segmentation methods requ...
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06/06/2021
Transformer in Convolutional Neural Networks
We tackle the low-efficiency flaw of vision transformer caused by the hi...
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05/23/2021
Boosting Crowd Counting with Transformers
Significant progress on the crowd counting problem has been achieved by ...
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12/16/2020
CompositeTasking: Understanding Images by Spatial Composition of Tasks
We define the concept of CompositeTasking as the fusion of multiple, spa...
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10/17/2020
LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
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07/03/2020
Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation
This paper studies the problem of learning semantic segmentation from im...
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12/14/2019
Fine-grained Recognition: Accounting for Subtle Differences between Similar Classes
The main requisite for fine-grained recognition task is to focus on subt...
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12/13/2019
Towards Partial Supervision for Generic Object Counting in Natural Scenes
Generic object counting in natural scenes is a challenging computer visi...
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05/30/2019
iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images
Existing Earth Vision datasets are either suitable for semantic segmenta...
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03/06/2019
Object Counting and Instance Segmentation with Image-level Supervision
Common object counting in a natural scene is a challenging problem in co...
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10/18/2017