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07/26/2023
MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation
We propose MAMo, a novel memory and attention frame-work for monocular v...
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06/09/2023
DIFT: Dynamic Iterative Field Transforms for Memory Efficient Optical Flow
Recent advancements in neural network-based optical flow estimation ofte...
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03/24/2023
DistractFlow: Improving Optical Flow Estimation via Realistic Distractions and Pseudo-Labeling
We propose a novel data augmentation approach, DistractFlow, for trainin...
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04/14/2022
Imposing Consistency for Optical Flow Estimation
Imposing consistency through proxy tasks has been shown to enhance data-...
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11/22/2021
MUM : Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection
Many recent semi-supervised learning (SSL) studies build teacher-student...
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03/09/2021
Deep Learning-based High-precision Depth Map Estimation from Missing Viewpoints for 360 Degree Digital Holography
In this paper, we propose a novel, convolutional neural network model to...
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06/03/2020
Interpolation-based semi-supervised learning for object detection
Despite the data labeling cost for the object detection tasks being subs...
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02/17/2020
Class-Imbalanced Semi-Supervised Learning
Semi-Supervised Learning (SSL) has achieved great success in overcoming ...
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11/19/2019
Tell Me What They're Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction
In this work, we introduce a novel weakly supervised object detection (W...
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07/17/2017
Residual Features and Unified Prediction Network for Single Stage Detection
Recently, a lot of single stage detectors using multi-scale features hav...
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06/30/2017
Superpixel-based Semantic Segmentation Trained by Statistical Process Control
Semantic segmentation, like other fields of computer vision, has seen a ...
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05/26/2017