Master Thesis : Robust deep feature matching for traffic sign matching
Do you want to create technology for the next generation of industry and society? Univrses is now looking for a Master Thesis student to join the team in Stockholm!
Univrses is a 3D Computer Vision and Machine Learning company based in Stockholm, creating high-end technologies for autonomous systems. We work in several different areas, but our main focus is on self-driving vehicles, mobile robotics and smart city development. Our team consists of hard-working and friendly people from all over the world with diverse backgrounds and expert knowledge in computer vision, robotics, machine learning, physics, math, software development and more.
Master Thesis at Univrses
Right now, we offer Master students the opportunity to be an integral part of the team while working on their Thesis. You will be working in a fun, stimulating and highly professional work environment together with our awesome team. This is truly a unique chance to work with some of the best scientists and engineers in Computer Vision and Robotics in the world.
Background
Finding correspondences between two images is a fundamental building block of many computer vision applications like camera tracking and 3D mapping. The most common approach to image matching relies on sparse interest points that are matched using high-dimensional representations encoding their local visual appearance. Reliably describing each point is challenging in conditions that exhibit symmetries, weak texture, or appearance changes due to varying viewpoints and lighting. To reject outliers that arise from occlusion and missing points, such representations should also be discriminative. This yields two conflicting objectives, robustness, and uniqueness, that are hard to satisfy.
To address these limitations, SuperGlue introduced a new paradigm – a deep network that considers both images at the same time to jointly match sparse points and reject outliers. It leverages the powerful Transformer model to learn to match challenging image pairs from large datasets.
Univrses need to uniquely identify features across several images captured from different viewpoints and with different lighting/seasons.

Goals
The primary objectives of this research are as follows:
- Deep feature matching for bounding box matching: How can these point-to-point matches be extended to bounding box to bounding box matching?
- Pretrained models vs fine-tuned model: What are the performances of the pretrained model on our data? Do we benefit from fine-tuning them on our data?
- Robustness evaluation: How robust is it to large point of view changes, temporal changes (time of the day, time of the year), repetitive patterns?
Relevant material
- Feature matching:
- Feature extractors:
Easily test different image-matching solutions here: Image Matching Webui - a Hugging Face Space by Realcat
Required background
Applicants are expected to possess a comprehensive understanding of deep learning and computer vision, which will be essential for engaging with the research effectively.
Proficiency in Python coding is a prerequisite for implementing and experimenting with the proposed techniques.
Required application material
- CV
- Cover letter
- Transcripts (with grades)
All application material must be in English.
The work is supposed to start in January 2024
Next step
Interested in joining Univrses as our new Master Thesis student? Submit your application - All application material must be in English!
- Department
- Tech
- Role
- Master Thesis Student
- Locations
- Stockholm
- Remote status
- Temporarily Remote
Stockholm
Working at Univrses
-
World-leading technologies
You will work with unique solutions that will change the way industries operate and societies develop -
World-leading team
You will work in a diverse and friendly team with the world's most skilled scientists and expert engineers within the field -
Generous employee benefits
You will be offered a competitive salary, flexible work hours, pension plan and weekly Lunch&Learns, among other things -
Offices in the center of Stockholm
During non-pandemic times, you will work from our bright and spacious facilities in the heart of Södermalm, Stockholm
About Univrses
Univrses is a 3D Computer Vision and Machine Learning company, based in Sweden. We create high-end technologies for autonomous systems, and specialize in self-driving vehicles, mobile robotics and smart city development. The team consists of programmers and PhDs within fields such as computer vision, machine learning, robotics, software development, maths and physics.
Master Thesis : Robust deep feature matching for traffic sign matching
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