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関連する概念動画

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

787
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
787
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

568
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
568
Deconvolution01:20

Deconvolution

647
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
647
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

681
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
681
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

1.4K
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
1.4K
Diffusion01:21

Diffusion

6.9K
Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
6.9K

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関連する実験動画

Updated: Mar 1, 2026

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

815

ReconX: Video拡散モデルを用いた疎視点からのあらゆるシーンの再構築

Fangfu Liu, Wenqiang Sun, Hanyang Wang

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |February 27, 2026
    PubMed
    まとめ
    この要約は機械生成です。

    ReconXは、疎視点からの3Dシーン再構築をビデオ生成タスクとして扱います。この新しいアプローチは、大規模なビデオ拡散モデルを活用して、限られた画像から一貫性のある詳細な3Dシーンを作成します。

    科学分野:

    • コンピュータビジョン
    • 3Dグラフィックス
    • 人工知能
    キーワード:
    3Dシーン再構築疎視点再構築ビデオ拡散モデル生成モデル3Dグラフィックス

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    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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    関連する実験動画

    Last Updated: Mar 1, 2026

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    Published on: June 27, 2025

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    Computer-Generated Animal Model Stimuli
    26:43

    Computer-Generated Animal Model Stimuli

    Published on: July 29, 2007

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    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

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    背景:

    • 2D画像から3Dモデルへの再構築は、密視点シナリオで大きな成功を収めています。
    • 疎視点3D再構築は依然として不良設定問題であり、アーティファクトや歪みにつながります。

    結論:

    • ReconXは、疎視点からの3Dシーン再構築のための強力な新しいアプローチを提供します。
    • ビデオ拡散モデルからの生成的プライオアの使用は、再構築の精度と一貫性を向上させます。
    • 提案手法は、特に挑戦的な疎視点シナリオにおいて、3D再構築の分野を進歩させます。