image is everything
play

Image Is Everything Go With A Pro Why Professional Real Estate - PowerPoint PPT Presentation

Jun 29, 2023 •706 likes •907 views

Image Is Everything Go With A Pro Why Professional Real Estate Photography Works: 1. Professional Photography holds a buyers attention for at least 20 seconds compared to 2 seconds without images. (marketleader.com) 2. Listings with

  1. Image Is Everything

  2. Go With A Pro Why Professional Real Estate Photography Works: 1. Professional Photography holds a buyer’s attention for at least 20 seconds compared to 2 seconds without images. (marketleader.com) 2. Listings with photographs taken by pros sold for $3,400 to $11,200 more than their initial listing price. (Leading National Brokerage) 3. Listings that feature professional photography receive 61% more views. (wsj.com) 4. 84% of homebuyers cited they wouldn’t even consider a property if the listing didn’t have photography. (cbsnews.com) 5. 83% of homebuyers find professional real estate photography “very useful” during the decision-making process. (propertiesonline.com)

  3. The VHT Studios Advantage  Founded in 1998  Over 1 Million Properties Photographed  Over 10 Million Rooms Photographed  Over $200 Billion In Properties Photographed  250 of the nation’s top Professional Real Estate & Architectural Photographers call VHT Studios their home

  4. The Professional Difference is Clear! Amateur VHT Studios Photograph Photograph

  5. The Professional Difference is Clear! Amateur VHT Studios Photograph Photograph

  6. The Professional Difference is Clear! Amateur VHT Studios Photograph Photograph

  7. Products & Services

  8. Photography Services Signature Premium

  9. Photography Services Signature Premium

  10. Studio Enhancements Replace Green Grass Before After

  11. Studio Enhancements Blue Sky Upgrade Before After

  12. Drone/Aerial Photography & Video Drone/Aerial Sample

  13. Interactive Floor Plans

  14. Virtual Staging Before After -Help homebuyers envision the potential of a vacant property or an empty room -A depiction of how spaces can be furnished and decorated -Choose from our carefully curated collection of furniture and décor options Virtual Staging Samples

  15. Paint Before After -Visualize the beauty of a space without lifting an actual paintbrush -Virtually change any flat surface to any color you choose -Remove dated wallpaper or add a bright accent wall Virtual Staging Samples

  16. Virtual Declutter Before After -A post-shoot solution for unwanted clutter; from a messy coffee tables and kitchen countertops to disorderly bookshelves and more -Removes any items that interferes with visualizing the full potential of a space -Gets rid of clutter while leaving major furnishings in the room Virtual Staging Samples

  17. Virtual Redecorate Before After -The ultimate transformation -Remove existing furniture and décor down to bare walls, ceilings and floors; anything short of structural changes -Completely redecorate the space by changing furnishings, décor, flooring or wall colors Virtual Staging Samples

  18. 3-D Tours

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Image Restoration Image Enhancement and Image Restoration both deal with improving images. Image

Image Restoration Image Enhancement and Image Restoration both deal with improving images. Image

Image Restoration Image Enhancement and Image Restoration both deal with improving images. Image Analysis In Image Enhancement, the quality of the improved image was Image Restoration and Reconstruction judged subjectively. In contrast, Image

349 views • 8 slides
Image Features Sanja Fidler CSC420: Intro to Image Understanding 1 / 1 Image Features Image

Image Features Sanja Fidler CSC420: Intro to Image Understanding 1 / 1 Image Features Image

Image Features Sanja Fidler CSC420: Intro to Image Understanding 1 / 1 Image Features Image features are useful descriptions of local or global image properties designed (or learned!) to accomplish a certain task You may want to choose di ff

941 views • 70 slides
Image formation How are objects in the world captured in Image formation an image? Matlab

Image formation How are objects in the world captured in Image formation an image? Matlab

Image formation How are objects in the world captured in Image formation an image? Matlab tutorial Tuesday, Sept 2 Image formation Physical parameters of image formation object film Geometric Type of projection Camera

190 views • 8 slides
Image Transforma1ons image filtering : change range of image Image Processing : g(x) =

Image Transforma1ons image filtering : change range of image Image Processing : g(x) =

Image Transforma1ons image filtering : change range of image Image Processing : g(x) = h(f(x)) Transforma1ons, Warping and Morphing h Last Week Courtesy: Irfan Essa, Georgia Tech James Hayes, Georgia Tech Alexei Efros, UC Berkeley

308 views • 6 slides
Image Features Sanja Fidler CSC420: Intro to Image Understanding 1 / 64 Image Features Image

Image Features Sanja Fidler CSC420: Intro to Image Understanding 1 / 64 Image Features Image

Image Features Sanja Fidler CSC420: Intro to Image Understanding 1 / 64 Image Features Image features are useful descriptions of local or global image properties designed to accomplish a certain task You may want to choose different features

1.09k views • 71 slides
Technological development and use across disciplines Image: ESA/ATG Medialab Image: CAGE, UiT

Technological development and use across disciplines Image: ESA/ATG Medialab Image: CAGE, UiT

Technological development and use across disciplines Image: ESA/ATG Medialab Image: CAGE, UiT Image: NTNU Applied underwater robotics Lab RV Kronprins Haakon Image/data: nuka.uib.no Selected Norwegian marine observations in the Arctic

272 views • 3 slides
Chapter 4 IMAGE PROC IMAGE PROCESSIN ESSING ILWIS for Windows contains a set of image

Chapter 4 IMAGE PROC IMAGE PROCESSIN ESSING ILWIS for Windows contains a set of image

Chapter 4 IMAGE PROC IMAGE PROCESSIN ESSING ILWIS for Windows contains a set of image processing tools for enhancement and analysis of data from space borne or airborne platforms. In this chapter, the routine applications such as image

1.22k views • 88 slides
Image Resizing / Goal: Mimic a be7er photographer by Retarge.ng improving image quality

Image Resizing / Goal: Mimic a be7er photographer by Retarge.ng improving image quality

10/4/16 Advanced Image Edi.ng Tools Image Resizing / Goal: Mimic a be7er photographer by Retarge.ng improving image quality Image retarge.ng (resize image) Image comple.on (erase and fill unwanted areas) Texture synthesis

340 views • 10 slides
IM IMAGE-TO TO-IM IMAGE T TRANSLATIO ION W WIT ITH C CONDIT ITIO IONAL AD ADVERSAR

IM IMAGE-TO TO-IM IMAGE T TRANSLATIO ION W WIT ITH C CONDIT ITIO IONAL AD ADVERSAR

IM IMAGE-TO TO-IM IMAGE T TRANSLATIO ION W WIT ITH C CONDIT ITIO IONAL AD ADVERSAR ARIAL AL NETWORKS Yuanjie Lu 9 th April What is image to image? Seems like a language concept can be translated into Chinese, French, Italian,

462 views • 17 slides
Is Digital Technology Image 1 Restructuring the brain? Globally connected Image 2 Image 3 How

Is Digital Technology Image 1 Restructuring the brain? Globally connected Image 2 Image 3 How

Is Digital Technology Image 1 Restructuring the brain? Globally connected Image 2 Image 3 How do we interact? Image 4 Image 5 What do others think? Young people are born into technology, and theyre used to using it 24/7, their brains

614 views • 15 slides
Image Processing Todays Class Image Representations: Matrices Image Representations: RGB,

Image Processing Todays Class Image Representations: Matrices Image Representations: RGB,

CS6501: Deep Learning for Visual Recognition Image Processing Todays Class Image Representations: Matrices Image Representations: RGB, HSV, etc Image Processing: Brightness Image Filtering: Mean Filter, Median Filter Image Filtering:

959 views • 77 slides
RGBD Tutorial 14210240041 Gu Pan Image RGB YUV Lab Depth Image RGB image Depth image Each pixel in

RGBD Tutorial 14210240041 Gu Pan Image RGB YUV Lab Depth Image RGB image Depth image Each pixel in

RGBD Tutorial 14210240041 Gu Pan Image RGB YUV Lab Depth Image RGB image Depth image Each pixel in depth image shows the distance to camera Device Kinect Kinect2 (we use) SoftKinetic Leapmotion Kinect Depth camera developed by

480 views • 29 slides
The Digital Image What is a Digital Image? How to Make an Image a Computable Entity

The Digital Image What is a Digital Image? How to Make an Image a Computable Entity

The Digital Image What is a Digital Image? How to Make an Image a Computable Entity Convert 3D Scene to a 2D Computational Photography ] CS 4475/6475 Maria Hybinette Today: How the digital information of the sensor can be used

568 views • 7 slides
Introduction: What is Image Processing? CS 4640: Image Processing Basics January 10, 2012 What

Introduction: What is Image Processing? CS 4640: Image Processing Basics January 10, 2012 What

Introduction: What is Image Processing? CS 4640: Image Processing Basics January 10, 2012 What is Image Processing? Definition Image processing is the study of any algorithm that takes an image as input and returns an image as output.

530 views • 16 slides
YIN XU 1. Image Segmentaion & Retrieval What is image segmentation? Whats the

YIN XU 1. Image Segmentaion & Retrieval What is image segmentation? Whats the

CS688: Large-Scale Image & Video Retrieval (Spring 2020) YIN XU 1. Image Segmentaion & Retrieval What is image segmentation? Whats the relationship to image retrieval? 2. Current challenges & solutions: Challenges: Intra-class

239 views • 23 slides
Deep Learning in Image Processing Topics: Image Filtering 101 CNNs 101 Image

Deep Learning in Image Processing Topics: Image Filtering 101 CNNs 101 Image

Deep Learning in Image Processing Topics: Image Filtering 101 CNNs 101 Image Processing Pipelines Frank Dellaert CS 4476 Computer Vision Many slides from Stanfords CS231N by Fei-Fei Li, Justin Johnson, Serena Yeung, as well as

1.46k views • 79 slides
September 15, 2018 TSX-V: JG OTCQB: JGLDF Forward-looking Statements Certain of the statements

September 15, 2018 TSX-V: JG OTCQB: JGLDF Forward-looking Statements Certain of the statements

Corporate Presentation September 15, 2018 TSX-V: JG OTCQB: JGLDF Forward-looking Statements Certain of the statements made and information contained herein is forward - looking information within the meaning of the Briti sh Columbia

439 views • 26 slides
Satellite Based Pollution Monitoring in Prince William Sound Final Presentation to Prince

Satellite Based Pollution Monitoring in Prince William Sound Final Presentation to Prince

Satellite Based Pollution Monitoring in Prince William Sound Final Presentation to Prince William Sound Regional Citizens Advisory Council May 6, 2016 Outline Introduction Approach Results Conclusions and Recommendations

562 views • 23 slides
Using Neural Cells to Improve Image Textual Line Segmentation Patrick Schone

Using Neural Cells to Improve Image Textual Line Segmentation Patrick Schone

Using Neural Cells to Improve Image Textual Line Segmentation Patrick Schone (patrickjohn.schone@ldschurch.org) 7 February 2017 Standards Technical Conference Overview Motivation Neural Cells for Line Counting Hybrid Segmentation

668 views • 18 slides
Good evening everyone, and thank you for coming. My name is Chris Corliss and I am the

Good evening everyone, and thank you for coming. My name is Chris Corliss and I am the

Good evening everyone, and thank you for coming. My name is Chris Corliss and I am the Manager of the Louis Bergers Solid Waste Services Group. We are working on behalf of the New Jersey Department of Environmental Protection on the

852 views • 25 slides
EIB -ACP Climate Action Moses Wekesa Business Development Director Disclaimer: No part of this

EIB -ACP Climate Action Moses Wekesa Business Development Director Disclaimer: No part of this

This image cannot currently be displayed. EIB -ACP Climate Action Moses Wekesa Business Development Director Disclaimer: No part of this report may be circulated, quoted, or reproduced for distribution without prior written approval from

605 views • 15 slides
Depth Prediction and RGBD Images for Recognition Yihui He, Metehan Ozten yihuihe@foxmail.com, m

Depth Prediction and RGBD Images for Recognition Yihui He, Metehan Ozten yihuihe@foxmail.com, m

Depth Prediction and RGBD Images for Recognition Yihui He, Metehan Ozten yihuihe@foxmail.com, m ozten@umail.ucsb.edu May 25, 2016 Yihui He, Metehan Ozten Depth Prediction and RGBD Images for Recognition Related work and motivation Yihui He,

510 views • 21 slides
T E C H N O L O G Y R E G U L AT I O N , C L I M AT E C H A N G E , A N D A I Survey Results

T E C H N O L O G Y R E G U L AT I O N , C L I M AT E C H A N G E , A N D A I Survey Results

T E C H N O L O G Y R E G U L AT I O N , C L I M AT E C H A N G E , A N D A I Survey Results January 8 13, 2020 Climate change and consumer data protection are greatly concerning to respondents in the I B M T E C H N O L O G Y U.S. and

1.3k views • 35 slides
The STIS Calibration Pipeline S.J. Hulbert and P.E. Hodge Space Telescope Science Institute, 3700

The STIS Calibration Pipeline S.J. Hulbert and P.E. Hodge Space Telescope Science Institute, 3700

1997 HST Calibration Workshop Space Telescope Science Institute, 1997 S. Casertano, et al., eds. The STIS Calibration Pipeline S.J. Hulbert and P.E. Hodge Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 Abstract.

269 views • 5 slides

More recommend