Browse State-of-the-Art › Occlusion Handling
Occlusion Handling
25 papers with code · 0 benchmarks · 5 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
5 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
25 shown of 25 papers with code (93 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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8 Jun 2020 5 repositories listed Syntology ran 1 of 17 samples · 16 unverifiedWe systematically compare and analyze a set of key components in unsupervised optical flow to identify which photometric loss, occlusion handling, and smoothness regularization is most effective.
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28 May 2024 3 repositories listedSpecifically, we exploit the 2D detections and extracted features from multiple cameras to provide a better approximation of the multi-object filtering density to realize the track initiation/termination and…
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11 Jul 2024 2 repositories listedIn occlusion handling, the filter's efficacy is dictated by trade-offs between the sophistication of the occlusion model and computational demand.
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17 Dec 2019 2 repositories listedWe investigate applying convolutional neural network (CNN) architecture to facilitate aerial hyperspectral scene understanding and present a new hyperspectral dataset-AeroRIT-that is large enough for CNN training.
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28 May 2025 1 repository listedTo enable dynamic modeling, we propose a dynamic editing module during training to enhance the renderings by editing the positions of the vehicles.
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26 May 2025 1 repository listedWhile virtual try-on has achieved significant progress, evaluating these models towards real-world scenarios remains a challenge.
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14 Apr 2025 1 repository listedComplex video object segmentation continues to face significant challenges in small object recognition, occlusion handling, and dynamic scene modeling.
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17 Mar 2025 1 repository listedFor cow detection, we fine-tuned 28 models (25 YOLO variants, 3 transformers) on 600 frames, testing on the full video.
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26 Feb 2025 1 repository listedThis paper introduces the Emirates Multi-Task (EMT) dataset - the first publicly available dataset for autonomous driving collected in the Arab Gulf region.
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OccludeNet: A Causal Journey into Mixed-View Actor-Centric Video Action Recognition under Occlusions24 Nov 2024 1 repository listedWe anticipate that the challenges posed by OccludeNet will stimulate further exploration of causal relations in occlusion scenarios and encourage a reevaluation of class correlations, ultimately promoting sustainable…
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1 Jun 2024 1 repository listedWe validate our novel approach using the MP-100 benchmark, a comprehensive dataset spanning over 100 categories and 18, 000 images.
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21 Mar 2023 1 repository listedThis paper presents a novel approach for estimating human body shape and pose from monocular images that effectively addresses the challenges of occlusions and depth ambiguity.
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6 Aug 2022 1 repository listedData association is a crucial component for any multiple object tracking (MOT) method that follows the tracking-by-detection paradigm.
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15 Jun 2022 1 repository listedObject detection and semantic segmentation with the 3D lidar point cloud data require expensive annotation.
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8 Mar 2022 1 repository listedOur experiments demonstrate the effectiveness of the proposed framework for handling the missing joints as well as quantification of the occlusion handling capability of the deep neural networks.
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1 Jan 2022 1 repository listedLabeled real data of occlusions is scarce (even in large datasets) and synthetic data leaves a domain gap, making it hard to explicitly model and learn occlusions.
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8 Sep 2021 1 repository listedLocalizing stereo boundaries and predicting nearby disparities are difficult because stereo boundaries induce occluded regions where matching cues are absent.
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16 May 2021 1 repository listedThe ability to simultaneously track and reconstruct multiple objects moving in the scene is of the utmost importance for robotic tasks such as autonomous navigation and interaction.
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23 Mar 2021 1 repository listed Syntology ran 7 of 12 samples · 5 unverifiedSegmenting highly-overlapping objects is challenging, because typically no distinction is made between real object contours and occlusion boundaries.
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6 Mar 2021 1 repository listedIn contrast, there are algorithms that only use motion cues to increase speed, especially for online applications.
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7 Nov 2020 1 repository listedAlthough recent years have witnessed the great advances in stereo image super-resolution (SR), the beneficial information provided by binocular systems has not been fully used.
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29 Jun 2020 1 repository listedWe introduce an energy and level-set optimizer that improves boundaries by encoding the essential geometry of occlusions: The spatial extent of an occlusion must equal the amplitude of the disparity jump that causes it.
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Vid2Curve: Simultaneous Camera Motion Estimation and Thin Structure Reconstruction from an RGB Video7 May 2020 1 repository listedWe propose the first approach that simultaneously estimates camera motion and reconstructs the geometry of complex 3D thin structures in high quality from a color video captured by a handheld camera.
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21 Apr 2020 1 repository listedWe present a novel multi-attentional convolutional architecture to tackle the problem of real-time RGB-D 6D object pose tracking of single, known objects.
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26 Apr 2019 1 repository listedThe majority of approaches for acquiring dense 3D environment maps with RGB-D cameras assumes static environments or rejects moving objects as outliers.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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