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The AI market will offer thousands of workplaces in the upcoming years. Polish kids with incredible math skills can lead the world’s research programs, but a lot of them live in small villages with sub-optimal learning conditions. So far, we have helped more than 2200 primary and secondary school students to start their career in AI with our free classes, and that’s only the beginning of the AI Schools &amp; Academy project.&nbsp;

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Our children, the future&nbsp;

As a responsible company based on meritocracy, we support various initiatives creating gender-equal society. We employ many female PhDs, experts and professionals. Synerise empowers girls and women to join the STEM industry and start career with AI, Data Science or math-related fields. As a Microsoft Official Partner, we took part in Alice Envisions the Future, an event for talented young girls.&nbsp;

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AI has no gender&nbsp;

The power of science is driving the wheels of the economy and global wealth. We support students of different AI-related fields with our experience and knowledge. We established PhD studies in Data Science at the Poznan University of Economics. Synerise CEO Jarosław Królewski is the founder of several innovative teaching programs (inter alia: Social Informatics, Digital Economy, Digital Marketing) at AGH University of Science and Technology. He is also an author of several books issued by the largest publishing houses (inter alia PWN) in Poland and worldwide (Cambridge Scholars Publishing).&nbsp;

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Thought leadership

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We work hard and think hard, always searching for a space to evolve our solutions, to help our clients spread their wings and maximize the effects of joint work. We believe that everything starts with a strong mindset and we proudly support those who also work hard to achieve success, no matter the field. That’s why we help young and promising sportsmen like Miłosz Sowiński, one of the best talents of triathlon and the youth academy of Wisła Kraków football team.&nbsp;

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Harder, Better, Faster, Stronger&nbsp;

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We have recently published <a href="https://arxiv.org/pdf/2003.04094.pdf" target="_blank" rel="noopener noreferrer nofollow">paper</a> about fashion retrieval. During our research ‪we achieved 54.8 mAP, 72.9 Acc@20 on Street2Shop and 47.3 Acc@1, 79.0 Acc@20 on DeepFashion dataset‬ - establishing new state-of-the-art results for both. We would like to share with You some ideas directly from our AI Lab. &nbsp;In the last 3 years, there's been a flood of research papers in AI and Machine Learning published by Chinese universities and companies. Strong incentives from government and industry, combined with the challenges of scale (almost 1.4Bn citizens) push the frontier of research in China forward at an impressive pace.Although the topics are quite diverse, there is a category of papers which are overrepresented when compared to western research institutions' output. The papers cover various topics, but their possible applications are common: mass surveillance. [10],[9],[2],[6],[1],[5],[8]One of the most popular applications of AI, is that of Person Re-Identification - which is linking the photos/videos from CCTV cameras to identities of citizens. As you can imagine, the task is quite challenging, due to various factors:<ul><li>cameras have different quality</li><li>angles, lighting &amp; visibility conditions vary</li><li>people can be partially occluded</li><li>people change clothes, put on hats, can wear sunglasses etc.</li><li>people travel between different areas, so location information is of limited usability</li><li>human body is capable of many different poses and movements</li><li>much more variety is present in the real-world compared to synthetic datasets.</li></ul>While tracking the progress made by China is scary, yet fascinating, can their state-sponsored research be re-purposed to directly benefit the end-user?In our paper [7] we propose an approach adapted from mass surveillance, which with some modifications, outperforms all prior research in fashion visual search.The problem of fashion retrieval / visual search sounds simple - given a user-made photo of a clothing item, automatically pick most similar clothes from a store's assortment. The user may take a photo of his/her friend, a photo of an item in a store, or upload a photo found in the Internet.<figure class="image"><img src="/uploads/92ee67516f1146168fea60107f1c34a0.jpeg"></figure>&nbsp;<figure class="image"><img src="/uploads/5793287d0e2a4bae8a40682d0bbafcb2.png"></figure>Intuitively, representation learning should "distill the essence of visual identity and similarity" of objects, and disregard all modifications &amp; transformations of input, which do not change similarity or identity.Some examples of transformations which do not change visual identity/similarity:<ul><li>facial expressions - while they can deform the face, they do not change a person's identity</li><li>clothes deformability - a crumpled sweater is still the same sweater</li><li>lighting, brightness, contrast, etc. - objects remain the same, while they look different</li><li>view angles, rotations, focal length, image resolution - they change the photo, but have no effect on the objects themselves</li></ul><figure class="image"><img src="/uploads/8ae1a1e73de046cdb5dce5e855441abe.png"><figcaption>Source: BU-3DFE dataset facial expressions</figcaption></figure>There are a lot more real-world transformations which can confuse ML models, but are naturally disregarded by people when evaluating "identity" or "similarity", e.g. weather conditions, mechanical transformations etc. Visual representation learning aims to be resistant to these transformations.<figure class="image"><img src="/uploads/4a37856354f74898924e4da893425c42.png"></figure>When it comes to fashion, we're interested in vector representations of clothes, where the same "fashion item" gets the same or similar vectors, regardless of where, when and how the photo was taken. In contrast, when it comes to mass surveillance, we'd be interested in vector representations of people, where the same person get the same or similar vectors, regardless of where, when and how the photo was taken, what the person was wearing and what pose they were photographed in.The two use-cases sound so much alike, that it's quite surprising that very little intellectual cross-pollination has happened between these areas until now.<figure class="image"><img src="/uploads/1fdf689c8630407f8b9518e8bba76c8e.png"></figure><figure class="image"><img src="/uploads/d3cf849c83bd444c9351600402016bb8.png"></figure>In our paper [7], we identify the similarities and differences between fashion and mass surveillance in depth. Then we successfully transfer latest research from Person Re-Identification to fashion retrieval for visual search.While the Person ReID models require some adjustments to work well on fashion datasets, the final results are quite extraordinary. Our best approach outperforms all prior published research in fashion retrieval and establishes new state-of-the art results on two commonly used datasets - DeepFashion and Street2Shop. The best model described in the paper is a foundation of our Visual Search product at Synerise, trained on our massive proprietary datasets.<figure class="image"><img src="/uploads/cde7e5214f1c4ba7861baee6a9ec6b68.png"></figure><figure class="image"><img src="/uploads/54c57fc3db5046e79c3d2fcd1649a23f.png"></figure>What's especially worth noting, is that our strong baseline model is much simpler than some of the recent fashion-specific approaches. The simplicity is apparent with regard to architecture, training procedure and computational resources required.This should serve as a reminder that good foundations, proper abstractions and picking the right problem to solve are often key to unlocking significant progress in research. As unlikely as it sounds, fashion and surveillance have a lot in common when thinking in the framework of representation learning.Here are some example results of our best model:<figure class="image"><img src="/uploads/57b12ba51c29453ea8be59a3150d2cca.png"></figure><figure class="image"><img src="/uploads/14f26899d7854cc0acef6c2da7829a6c.png"></figure><figure class="image"><img src="/uploads/3a15b5daf21840d39ada7f9e9eae3e2d.png"></figure><figure class="image"><img src="/uploads/454482facc9a42e3adb645e0ddd9f5e2.png"></figure>For more details &amp; nice pictures check out our paper with the appendix: [7].Jacek Dąbrowski / Jarek Krolewski[1] Dong, C. et al. 2019. DeepMEF: A Deep Model Ensemble Framework for Video Based Multi-modal Person Identification. Proceedings of the 27th ACM International Conference on Multimedia (Nice, France, Oct. 2019), 2531–2534.[2] Guo, Y. et al. 2019. Multi-Scale Convolutional Recurrent Neural Network with Ensemble Method for Weakly Labeled Sound Event Detection. 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) (Sep. 2019), 1–5.[3] Kuang, Z. et al. 2019. Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid. arXiv:1908.11754 [cs]. (Aug. 2019).[4] Kucer, M. and Murray, N. 2019. A Detect-Then-Retrieve Model for Multi-Domain Fashion Item Retrieval. CVPR Workshops. 10.[5] Nie, J. et al. 2019. Understanding personality of portrait by social embedding visual features. Multimedia Tools and Applications. 78, 1 (Jan. 2019), 727–746.[6] Song, W. et al. 2019. Partial Attribute-Driven Video Person Re-Identification. 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI) (Nov. 2019), 539–546.[7] Wieczorek, M. et al. 2020. A Strong Baseline for Fashion Retrieval with Person Re-Identification Models. arXiv:2003.04094 [cs]. (Mar. 2020).[8] Wu, L. et al. 2019. A Neural Influence Diffusion Model for Social Recommendation. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (Paris, France, Jul. 2019), 235–244.[9] Zhang, X. et al. 2019. TVV: Real-Time Visual Identity and Tracking with Edge Computing. Proceedings of the 2019 International Conference on Embedded Wireless Systems and Networks (Beijing, China, Mar. 2019), 419–424.[10] Zhang, Z. et al. 2018. Billion-Scale Network Embedding with Iterative Random Projection. 2018 IEEE International Conference on Data Mining (ICDM) (Nov. 2018), 787–796.

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Fashion retrieval is the challenging task of finding an exact match for fashion items contained within an image. Difficulties arise from the fine-grained nature of clothing items, very large intra-class and inter-class variance. Additionally, query and source images for the task usually come from different domains - street photos and catalogue photos respectively. Due to these differences, a significant gap in quality, lighting, contrast, background clutter and item presentation exists between domains. As a result, fashion retrieval is an active field of research both in academia and the industry.  Inspired by recent advancements in Person Re-Identification research, we adapt leading ReID models to be used in fashion retrieval tasks. We introduce a simple baseline model for fashion retrieval, significantly outperforming previous state-of-the-art results despite a much simpler architecture. We conduct in-depth experiments on Street2Shop and DeepFashion datasets and validate our results. Finally, we propose a cross-domain (cross-dataset) evaluation method to test the robustness of fashion retrieval models.

A Strong Baseline for Fashion Retrieval with Person Re-Identification Models

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Our Latest Scientific Paper With State-of-the-art results

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Synerise cooperates with Orange Polska, the market leader in mobile telecommunications, internet and data transmission, by supporting their digital transformation and providing customers with the best experience of using modern technologies. Synerise solutions help Orange acquire and retain satisfied customers, driving an increase in the share of digital channels in overall sales.

Building better customer experience and growth in e-commerce

Case study

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For nearly four decades, YES has been cultivating its ability to design jewelry that is both timeless and contemporary for the Polish market. This desire to constantly innovate and create prompts YES to offer original collections that reflect the experience, style and spirit of the times.&nbsp;

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of recovered clients convert 24 hours after re-entering the site

YES says “yes” to Synerise

Jewelry case study

At Synerise we've mastered remote work as we've always been open to it and more than 10% of our staff is 100% remote on a daily basis, reaching us from different parts of the world through Microsoft Teams, Slack and other platforms.&nbsp;What's more, the team employed on site (in the offices in Warsaw, Krakow, Poznan) has always had the possibility of unlimited remote work. All employees had to do was tell their team leader in advance and let the rest of the team know before that they were planning a home office on a given day. In this way, each of our employees has experience in working from outside the office.&nbsp;However, even though we all know how to handle remote work, the current scenario is brand new to us. More than 220 of us are working from homes right now, and we have to make sure we’re doing it the best way possible.See what we do to keep motivation up!&nbsp;<h3>How do we deal with remote work in Synerise? &nbsp;</h3>We have decided to organize mandatory updates from each department daily to keep our employees informed and motivated. We present use cases, new implementations, client stories and inspirations that everyone can follow. This solution not only affects greater team visibility, but also helps us all to stay in sync - and helps us to learn something new about the company and Synerise capabilities.&nbsp;Each day from Monday to Friday, we meet virtually on Teams to discuss the most important things and to listen to each other. For 30 minutes, every member of the team has a chance to participate in the most exciting things we do as a company each day. &nbsp;<figure class="image"><img src="/uploads/bd1bc9a3c1bc42b6b19dfb5c292359d7.jpeg"><figcaption>An example of remote work at&nbsp;Synerise&nbsp;- a daily 30-minute inspiration call with dozens of people from across the company joining in&nbsp;</figcaption></figure>Such summaries are extremely valuable since we often tend to focus on the work of our own department. Thanks to these calls, we have the opportunity to look at the work of others, share ideas, be up to date and eventually even work out new things.&nbsp;In addition, each business team (in IT we do it always!), has implemented daily scrum sessions. We gather online at 11:00 to talk about current tasks and prioritization.&nbsp;But what, apart from group online meetings, can we do to mobilize ourselves to be even more productive?&nbsp;<h3>Ways to Defeat a Lack of Motivation&nbsp;</h3>Have you ever wondered which job levels work remotely the most frequently? &nbsp;According to data from <a href="https://www.owllabs.com/hubfs/Owl%20Labs%202019%20State%20of%20Remote%20Work%20Report%20PDF.pdf" target="_blank" rel="noopener noreferrer nofollow">Owl Labs’ 2019 State of Remote Work</a> report, jobs with the greatest percentage of remote workers are people hired at C-Level. &nbsp;Our current situation is giving everyone a chance to see what it’s like to be a senior manager. &nbsp;However, data gathered in this report also shows some doubts about “home offices”. It shows that managers whose employees work remotely usually face the following concerns:&nbsp;<figure class="image"><img src="/uploads/1af89c6e9be346a3b1e5b1de4db1afa6.jpg"></figure>Let's consider how to facilitate your daily work from home and be our own “remote manager”, encouraging us to not be distracted:&nbsp;1. Set a place to work - Of course, this does not have to be an office or separate work room; all you need is a neat desk or table without too much clutter. Most people prefer not to work on the couch to avoid the temptation to be too lazy. &nbsp;However, if this is your favorite place, allowing you to relax and focus, feel free to work here too. Whatever works, right? 😊&nbsp;2. Work out your daily routine - Do not work non-stop, for 24 hours, on weekends. We know that the laptop is tempting and so is working "after hours" instead of when you should be available to the rest of the team.&nbsp;Divide your day into working hours and non-working hours that you will devote to your family or hobby (of course, a hobby realized in this case from home). Try to start and finish work at the same hours every day; also avoid eating dinner in front of the computer.&nbsp;Also, try to dress as for work. Your morning should be like going to the office: eat breakfast, shower, get dressed normally, change position at work as you normally would. You can start at your desk, move to the kitchen and back again. The bedroom is never a good option. Take breaks for family talks — after all, in the office you also have time for small talk with your colleagues.&nbsp;3. Focus on clear communication – During our everyday work it's much easier for us to make contact with a colleague sitting at the desk next to us and talk about whatever’s keeping you busy at the time. Even if you can’t do it right away, there’s always a coffee break not too far away.&nbsp;At the moment, however, we do not have such an opportunity, so let's make sure that the emails we send and other forms of discussing projects are clear and specific.&nbsp;<h3>Tips and Tricks from Synerise Collegues&nbsp;</h3>&nbsp;These tips are just the basics. If you are interested in some more clever hacks for improving your working comfort and efficiency, check what our coworkers say:&nbsp;<figure class="image"><img src="/uploads/afbcba0b52854fa5b874aeb964985d5b.jpg"></figure><h3>Summing Up&nbsp;</h3>Take care of yourself but pay attention to the quality of your work. Remote work is the future standard so let's all try to learn something from our current situation.&nbsp;We hope that our advice will prove to be helpful and the transition to remote work, even for long periods, will be trouble-free and rewarding. &nbsp;

At Synerise we've mastered remote work as we've always been open to it and more than 10% of our staff is 100% remote on a daily basis, reaching us from different parts of the world through Microsoft Teams, Slack and other platforms.&nbsp;What's more, the team employed on site (in the offices in Warsaw, Krakow, Poznan) has always had the possibility of unlimited remote work. All employees had to do was tell their team leader in advance and let the rest of the team know before that they were planning a home office on a given day. In this way, each of our employees has experience in working from outside the office.&nbsp;However, even though we all know how to handle remote work, the current scenario is brand new to us. More than 220 of us are working from homes right now, and we have to make sure we’re doing it the best way possible.See what we do to keep motivation up!&nbsp;<h3>How do we deal with remote work in Synerise? &nbsp;</h3>We have decided to organize mandatory updates from each department daily to keep our employees informed and motivated. We present use cases, new implementations, client stories and inspirations that everyone can follow. This solution not only affects greater team visibility, but also helps us all to stay in sync - and helps us to learn something new about the company and Synerise capabilities.&nbsp;Each day from Monday to Friday, we meet virtually on Teams to discuss the most important things and to listen to each other. For 30 minutes, every member of the team has a chance to participate in the most exciting things we do as a company each day. &nbsp;<figure class="image"><img src="/uploads/bd1bc9a3c1bc42b6b19dfb5c292359d7.jpeg"></figure>An example of remote work at&nbsp;Synerise&nbsp;- a daily 30-minute inspiration call with dozens of people from across the company joining in&nbsp;Such summaries are extremely valuable since we often tend to focus on the work of our own department. Thanks to these calls, we have the opportunity to look at the work of others, share ideas, be up to date and eventually even work out new things.&nbsp;In addition, each business team (in IT we do it always!), has implemented daily scrum sessions. We gather online at 11:00 to talk about current tasks and prioritization.&nbsp;But what, apart from group online meetings, can we do to mobilize ourselves to be even more productive?&nbsp;<h3>Ways to Defeat a Lack of Motivation&nbsp;</h3>Have you ever wondered which job levels work remotely the most frequently? &nbsp;According to data from <a href="https://www.owllabs.com/hubfs/Owl%20Labs%202019%20State%20of%20Remote%20Work%20Report%20PDF.pdf">Owl Labs’ 2019 State of Remote Work</a> report, jobs with the greatest percentage of remote workers are people hired at C-Level. &nbsp;Our current situation is giving everyone a chance to see what it’s like to be a senior manager. &nbsp;However, data gathered in this report also shows some doubts about “home offices”. It shows that managers whose employees work remotely usually face the following concerns:&nbsp;<figure class="image"><img src="/uploads/1af89c6e9be346a3b1e5b1de4db1afa6.jpg"></figure>Let's consider how to facilitate your daily work from home and be our own “remote manager”, encouraging us to not be distracted:&nbsp;1. Set a place to work - Of course, this does not have to be an office or separate work room; all you need is a neat desk or table without too much clutter. Most people prefer not to work on the couch to avoid the temptation to be too lazy. &nbsp;However, if this is your favorite place, allowing you to relax and focus, feel free to work here too. Whatever works, right? 😊&nbsp;2. Work out your daily routine - Do not work non-stop, for 24 hours, on weekends. We know that the laptop is tempting and so is working "after hours" instead of when you should be available to the rest of the team.&nbsp;Divide your day into working hours and non-working hours that you will devote to your family or hobby (of course, a hobby realized in this case from home). Try to start and finish work at the same hours every day; also avoid eating dinner in front of the computer.&nbsp;Also, try to dress as for work. Your morning should be like going to the office: eat breakfast, shower, get dressed normally, change position at work as you normally would. You can start at your desk, move to the kitchen and back again. The bedroom is never a good option. Take breaks for family talks — after all, in the office you also have time for small talk with your colleagues.&nbsp;3. Focus on clear communication – During our everyday work it's much easier for us to make contact with a colleague sitting at the desk next to us and talk about whatever’s keeping you busy at the time. Even if you can’t do it right away, there’s always a coffee break not too far away.&nbsp;At the moment, however, we do not have such an opportunity, so let's make sure that the emails we send and other forms of discussing projects are clear and specific.&nbsp;<h3>Tips and Tricks from Synerise Collegues&nbsp;</h3>&nbsp;These tips are just the basics. If you are interested in some more clever hacks for improving your working comfort and efficiency, check what our coworkers say:&nbsp;<figure class="image"><img src="/uploads/afbcba0b52854fa5b874aeb964985d5b.jpg"></figure><h3>Summing Up&nbsp;</h3>Take care of yourself but pay attention to the quality of your work. Remote work is the future standard so let's all try to learn something from our current situation.&nbsp;We hope that our advice will prove to be helpful and the transition to remote work, even for long periods, will be trouble-free and rewarding. &nbsp;

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Due to the current situation related to coronavirus, on 5th of March, as one of the first companies in Poland, we have decided to arrange remote work for all employees.   We believe in the effectiveness and social responsibility of this change but it’s not a radical departure from our previous day-to-day activities. Lots of Synerise People work remotely every day since we cooperate in various offices all over the world.   However, we know that working from home, especially at the scale of the whole company, can be a real challenge. That’s why we’ve decided to share our knowledge about good remote work practices. 

How We Deal With Remote Work at Synerise

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