How to Create Training Videos for Your Employees

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Creating training videos is crucial for engaging and effective learning, leading to growth and prosperity of employees and business. Discover how to create videos to enhance employee performance and productivity.

Training videos have emerged as the most effective tool for employee onboarding.

It is understandable companies are reluctant to hire unqualified candidates. But many of these companies do not invest in creating effective training programs either.

Employee training, in fact, is one of the areas receiving the least attention. How can companies expect their employees to outperform competitors without effective training?

Many employers have not yet realized business and work culture have changed. To prevent employees from falling behind, companies must focus on initial training and retraining.

So, what should employers do to cultivate efficient and productive employees? The answer is simple: create training videos.

Today, we will discuss why focusing on training videos is preferable to text-based training. You will learn how to create effective training videos for your employees. This will be an enjoyable experience. Let’s get started.

What is a training video?

Training videos are instructional content designed to teach skills and impart knowledge. They also educate employees about workplace practices and policies.

They communicate job requirements and employee expectations. These videos are also used to convey both short-term and long-term company expectations to employees.

Like customer onboarding videos, training videos can educate new recruits about the intricacies of their job and the best practices for performing it. Employee training includes instruction on workplace behavior, interpersonal skills, and diversity training.

The training program goes beyond employee onboarding. It emphasizes the importance of continuous knowledge improvement and encourages employees to develop innovative and creative problem-solving skills.

Apple – Inclusion and Diversity ( )

Why invest in training videos for your employees?

Your presence here suggests we don’t need to convince you about the importance of training videos for your employees. However, we strongly urge you to approach the entire process of creating training videos with a serious mindset. It is crucial not to create training videos simply because others are doing the same.

The business environment, workplace technologies, and work culture, as well as policies, are evolving rapidly. Even the most skilled newcomers and experienced employees can be negatively impacted by the absence of an effective training program.

Implementing effective employee training programs can enhance their competence and confidence. Investing in training videos is a mutually beneficial endeavor for both the company and its employees. Here are several advantages to consider:

Training videos bring consistency

The use of videos brings about uniformity in training materials and fosters consistency in understanding information.

Unlike text-based materials, training videos minimize the risk of misunderstandings. By ensuring all employees receive the same training, they are aligned when it comes to executing their tasks.

Training videos are conveniently accessible on-demand, allowing employees to view them whenever and wherever necessary.

Additionally, employees can revisit the videos as needed. This consistent accessibility ensures the accuracy of information, reduces errors, and minimizes discrepancies which may arise due to a lack of readily available training resources.

Employee onboarding becomes simple and easy

According to Forrester Research, 75% of all employees prefer watching videos over reading text material.

Visual learning aids in better comprehension and retention of information. It’s easier for employees to grasp complex concepts when presented in an engaging video format.

Creating training videos offers numerous benefits for companies as well. By using training videos, companies can reduce costs associated with hiring trainers and organizing physical training sessions for each batch of employees.

Moreover, training videos minimize the time required for repetitive explanations, freeing up valuable human resources for other tasks.

Contrary to popular belief, creating training videos is not as expensive as one might think. You can record each lesson in-house and outsource the video editing process to reduce overall costs.

Employee efficiency and productivity increases

Without proper training, employees are left to devise their own methods to accomplish tasks. This can become laborious, inefficient, and time-consuming.

This Is precisely why companies implement training programs—to expedite onboarding and enhance efficiency.

Visual learning aids employees in acquiring knowledge more quickly and utilizing tried and tested methods to complete tasks.

When employees become more efficient and productive, work is completed at a faster pace, resulting in a higher return on investment for the company.

Additionally, this leads to increased customer satisfaction. Most importantly, productive employees are highly valued within the organization, increasing their chances of upward mobility.

Improves customer retention and business growth

The primary objective of training is to equip employees with the skills to provide improved service and enhance customer satisfaction.

Retaining customers is more cost-effective than acquiring new ones. Efficient employees foster loyalty and strengthen the relationship between the company and the customers. Consequently, this customer loyalty translates into repeat business, fostering better growth and return on investment (ROI) for the company.

Reduces employee turnover

Scouting, finalizing, and hiring new employees is an expensive process. Moreover, it is a challenging and time-consuming task.

According to the Centre for American Progress, the cost of hiring a new employee to perform the same job can amount to up to 20% of their salary. This bears significant importance.

Effective training videos not only enhance productivity but also foster loyalty and employee retention. A survey conducted by the go2HR Society revealed approximately 40% of employees tend to leave a company within the first 12 months due to the absence of an effective training program.

What are the different types of employee training videos?

An employee training program can encompass a wide range of video types. This is due to the multitude of topics that need to be covered, and categorizing them into different types of videos can facilitate easier learning for employees.

The following are the most common types of videos included in a training program:

Software screencast videos

Screen recording videos are extensively used nowadays in a wide range of industries, particularly in SaaS and other software industries.

It is rare to find a company that doesn’t utilize specialized software to run its business. Screen recordings serve multiple purposes, such as creating how-to videos, tutorials, and other educational materials to train employees. By incorporating voice-over, one can effectively explain the content displayed on the screen.

Difficulty level: Easy

Equipment required: Screen capture tool, basic video editor, and voice-over talent.

Instructor-led videos

Similar to traditional classroom coaching, the instructor in this format explains concepts while facing a camera.

To aid the explanation, a whiteboard or projector may be utilized to display key points during the training session.

To enhance the training videos and captivate the audience, text annotations and graphics can be incorporated during the editing process.

Difficulty level: Moderate

Equipment required: Camera or smartphone, tripod, video editor, and instructor.

Animated training videos

The utilization of animated videos is an excellent method for simplifying complex concepts. While a skilled instructor can provide explanations in straightforward terms, animated visuals have the ability to depict the concept in action. Animated videos have the power to breathe life into even the most mundane topics.

When it comes to creating animated training videos, there are options to develop them in-house or seek the assistance of professional animated video production companies.

Online platforms offer both free and premium animation tools. However, for the production of top-notch employee training videos, it is advisable to engage the services of an experienced animated video production company.

Difficulty level: Moderate

Equipment required: 2D or 3D animation maker software, voice-over talent.

Example: Learn how to manage people and be a better leader ( )

Interactive videos

Interactive videos elevate employee training to a new level. It’s gradually gaining acceptance in the corporate world for their remarkable effectiveness in tutoring and engaging employees.

These videos utilize a combination of visuals, images, graphics, animations, text, quizzes, audio, and more to train employees.

Rather than being mere spectators, employees actively participate in the storytelling process, fostering a dynamic learning experience.

Furthermore, interactive videos facilitate easy progress tracking, ensuring seamless monitoring of employee development.

Difficulty level: High

Equipment required: Camera, animation maker, voice-over talent, video editor, and more.

Scenario videos

This technique is not common yet holds great potential as a future employee training method.

Scenario training encompasses various approaches, such as role-play, interactive videos, online quizzes, games, and VR/AR technologies, to effectively train employees.

Even in this employees exhibit a high level of engagement, and it allows you to monitor their progress.

Difficulty level: High

Equipment required: Role-play script, camera, animation maker, voice-over talent, video editor, and more.

The ingredients of an effective training video

Not all companies succeed in creating exceptional training videos for their employees. While there is no fixed formula, there are certain key ingredients present in all effective training programs.

Adhering to these four points can assist you in developing highly effective training videos to cultivate efficient and productive employees.

Focus on the message and outcome

The initial step in creating a training video involves identifying the message and goal.

Define the desired learning outcome and then formulate the training material to facilitate the achievement of the goal. It is crucial to maintain a consistent focus on the identified outcome throughout the video.

Ensure the content and language remain simple. Avoid excessive use of technical jargon, overwhelming videos with an abundance of information, or including irrelevant content, as they can confuse viewers and diminish employee engagement.

Whenever possible, consider incorporating rewards for employees who excel in quizzes or assessment exercises during the training program. Recognizing and rewarding top performers is an effective way to motivate your team during the onboarding stage.

Develop videos with the audience in mind

Imagine you are tasked with creating a training video on software development processes. Your objective is to cover the fundamental aspects of software development, explaining key concepts and terminology, as well as addressing common challenges faced by newcomers.

It is vital to tailor these videos to the specific requirements of your intended audience. New trainees may not possess the same level of familiarity as experienced employees. It’s important to provide information suitable for their level of understanding.

In order to produce effective custom videos, thorough research must be conducted to understand the needs and expectations of the audience.

To gain valuable insights and perspectives on the audience, it is advisable to consult with members of relevant departments. They can offer valuable input and assist in refining the video content to better meet the needs of the audience.

Use the most suitable video type and format

The communication medium is just as crucial as the message itself. The selection of video format plays a significant role in influencing the effectiveness of the content and the response elicited from new employees.

In the previous section, we explored five types of videos you can utilize for employee training. However, it’s worth noting there are numerous other options, including corporate videos, discussion videos, and more.

Once again, it is essential to consider your audience’s preferences and tailor the choice of video content accordingly for effective training.

You must ensure that you do not share training videos outside of your organization and create landing pages with exclusive access for employees. 

Make short videos to prevent information overload

Employee training videos should not be treated like YouTube Shorts or TikTok videos. Therefore, it is important not to fall into the misconception that due to decreasing attention spans, micro videos (videos less than 60 seconds) must be created.

Conversely, creating long-form videos is also counterproductive. The key is to determine the appropriate length based on the message, script, and content of the video. 

Long videos have the potential to disengage viewers, and much of the information conveyed may be forgotten by the employees. If you have a significant amount of information to share, it is advisable to divide the content into segments. 


In Summary

Visual training is a game-changer. Training videos ensure a consistent and continuous access to valuable materials.

For employees, videos offer effective learning opportunities, enabling them to be more productive and fostering growth within the company.

From the employers’ perspective, training videos help cut costs associated with hiring trainers and conducting physical training sessions. Additionally, visual training reduces employee turnover and the expenses related to hiring new staff.

However, to reap the benefits of the training program, it is crucial to do it right. Employ the tips provided in this article to create training videos that yield efficient and productive employees.


Author bio:


Cristian Stanciu is a freelance video editor, owner and post-production coordinator of Veedyou Media – a company offering video animation services to marketing agencies, video production studios and brands all over the globe. You can catch up with him on his blog or on LinkedIn.





The post How to Create Training Videos for Your Employees appeared first on The 6Q Blog.

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DynIBaR: Space-time view synthesis from videos of dynamic scenes

Posted by Zhengqi Li and Noah Snavely, Research Scientists, Google Research

A mobile phone’s camera is a powerful tool for capturing everyday moments. However, capturing a dynamic scene using a single camera is fundamentally limited. For instance, if we wanted to adjust the camera motion or timing of a recorded video (e.g., to freeze time while sweeping the camera around to highlight a dramatic moment), we would typically need an expensive Hollywood setup with a synchronized camera rig. Would it be possible to achieve similar effects solely from a video captured using a mobile phone’s camera, without a Hollywood budget?

In “DynIBaR: Neural Dynamic Image-Based Rendering”, a best paper honorable mention at CVPR 2023, we describe a new method that generates photorealistic free-viewpoint renderings from a single video of a complex, dynamic scene. Neural Dynamic Image-Based Rendering (DynIBaR) can be used to generate a range of video effects, such as “bullet time” effects (where time is paused and the camera is moved at a normal speed around a scene), video stabilization, depth of field, and slow motion, from a single video taken with a phone’s camera. We demonstrate that DynIBaR significantly advances video rendering of complex moving scenes, opening the door to new kinds of video editing applications. We have also released the code on the DynIBaR project page, so you can try it out yourself.

Given an in-the-wild video of a complex, dynamic scene, DynIBaR can freeze time while allowing the camera to continue to move freely through the scene.


The last few years have seen tremendous progress in computer vision techniques that use neural radiance fields (NeRFs) to reconstruct and render static (non-moving) 3D scenes. However, most of the videos people capture with their mobile devices depict moving objects, such as people, pets, and cars. These moving scenes lead to a much more challenging 4D (3D + time) scene reconstruction problem that cannot be solved using standard view synthesis methods.

Standard view synthesis methods output blurry, inaccurate renderings when applied to videos of dynamic scenes.

Other recent methods tackle view synthesis for dynamic scenes using space-time neural radiance fields (i.e., Dynamic NeRFs), but such approaches still exhibit inherent limitations that prevent their application to casually captured, in-the-wild videos. In particular, they struggle to render high-quality novel views from videos featuring long time duration, uncontrolled camera paths and complex object motion.

The key pitfall is that they store a complicated, moving scene in a single data structure. In particular, they encode scenes in the weights of a multilayer perceptron (MLP) neural network. MLPs can approximate any function — in this case, a function that maps a 4D space-time point (x, y, z, t) to an RGB color and density that we can use in rendering images of a scene. However, the capacity of this MLP (defined by the number of parameters in its neural network) must increase according to the video length and scene complexity, and thus, training such models on in-the-wild videos can be computationally intractable. As a result, we get blurry, inaccurate renderings like those produced by DVS and NSFF (shown below). DynIBaR avoids creating such large scene models by adopting a different rendering paradigm.

DynIBaR (bottom row) significantly improves rendering quality compared to prior dynamic view synthesis methods (top row) for videos of complex dynamic scenes. Prior methods produce blurry renderings because they need to store the entire moving scene in an MLP data structure.

Image-based rendering (IBR)

A key insight behind DynIBaR is that we don’t actually need to store all of the scene contents in a video in a giant MLP. Instead, we directly use pixel data from nearby input video frames to render new views. DynIBaR builds on an image-based rendering (IBR) method called IBRNet that was designed for view synthesis for static scenes. IBR methods recognize that a new target view of a scene should be very similar to nearby source images, and therefore synthesize the target by dynamically selecting and warping pixels from the nearby source frames, rather than reconstructing the whole scene in advance. IBRNet, in particular, learns to blend nearby images together to recreate new views of a scene within a volumetric rendering framework.

DynIBaR: Extending IBR to complex, dynamic videos

To extend IBR to dynamic scenes, we need to take scene motion into account during rendering. Therefore, as part of reconstructing an input video, we solve for the motion of every 3D point, where we represent scene motion using a motion trajectory field encoded by an MLP. Unlike prior dynamic NeRF methods that store the entire scene appearance and geometry in an MLP, we only store motion, a signal that is more smooth and sparse, and use the input video frames to determine everything else needed to render new views.

We optimize DynIBaR for a given video by taking each input video frame, rendering rays to form a 2D image using volume rendering (as in NeRF), and comparing that rendered image to the input frame. That is, our optimized representation should be able to perfectly reconstruct the input video.

We illustrate how DynIBaR renders images of dynamic scenes. For simplicity, we show a 2D world, as seen from above. (a) A set of input source views (triangular camera frusta) observe a cube moving through the scene (animated square). Each camera is labeled with its timestamp (t-2, t-1, etc). (b) To render a view from camera at time t, DynIBaR shoots a virtual ray through each pixel (blue line), and computes colors and opacities for sample points along that ray. To compute those properties, DyniBaR projects those samples into other views via multi-view geometry, but first, we must compensate for the estimated motion of each point (dashed red line). (c) Using this estimated motion, DynIBaR moves each point in 3D to the relevant time before projecting it into the corresponding source camera, to sample colors for use in rendering. DynIBaR optimizes the motion of each scene point as part of learning how to synthesize new views of the scene.

However, reconstructing and deriving new views for a complex, moving scene is a highly ill-posed problem, since there are many solutions that can explain the input video — for instance, it might create disconnected 3D representations for each time step. Therefore, optimizing DynIBaR to reconstruct the input video alone is insufficient. To obtain high-quality results, we also introduce several other techniques, including a method called cross-time rendering. Cross-time rendering refers to the use of the state of our 4D representation at one time instant to render images from a different time instant, which encourages the 4D representation to be coherent over time. To further improve rendering fidelity, we automatically factorize the scene into two components, a static one and a dynamic one, modeled by time-invariant and time-varying scene representations respectively.

Creating video effects

DynIBaR enables various video effects. We show several examples below.

Video stabilization

We use a shaky, handheld input video to compare DynIBaR’s video stabilization performance to existing 2D video stabilization and dynamic NeRF methods, including FuSta, DIFRINT, HyperNeRF, and NSFF. We demonstrate that DynIBaR produces smoother outputs with higher rendering fidelity and fewer artifacts (e.g., flickering or blurry results). In particular, FuSta yields residual camera shake, DIFRINT produces flicker around object boundaries, and HyperNeRF and NSFF produce blurry results.

Simultaneous view synthesis and slow motion

DynIBaR can perform view synthesis in both space and time simultaneously, producing smooth 3D cinematic effects. Below, we demonstrate that DynIBaR can take video inputs and produce smooth 5X slow-motion videos rendered using novel camera paths.

Video bokeh

DynIBaR can also generate high-quality video bokeh by synthesizing videos with dynamically changing depth of field. Given an all-in-focus input video, DynIBar can generate high-quality output videos with varying out-of-focus regions that call attention to moving (e.g., the running person and dog) and static content (e.g., trees and buildings) in the scene.


DynIBaR is a leap forward in our ability to render complex moving scenes from new camera paths. While it currently involves per-video optimization, we envision faster versions that can be deployed on in-the-wild videos to enable new kinds of effects for consumer video editing using mobile devices.


DynIBaR is the result of a collaboration between researchers at Google Research and Cornell University. The key contributors to the work presented in this post include Zhengqi Li, Qianqian Wang, Forrester Cole, Richard Tucker, and Noah Snavely.

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