- CodeAdvancedNew
Fuse LiDAR and Camera for an Autonomous Yard Truck
You receive 6 hours of synced LiDAR + 4-camera ring data from yard operations, with 3D bounding-box labels for pedestrians, forklifts, and containers. Build a late-fusion module…
- Sensor Fusion
- Lidar Perception
- Object Detection
Robot Perception and Autonomy - CodeAdvancedNew
Reconstruct a Heritage Facade with Structure-from-Motion
You receive 250 phone photos of the facade plus 6 ground control points measured by a surveyor (used only for metric scaling and validation, not for reconstruction). Run SfM to …
- Structure From Motion
- Multi View Stereo
- 3d Reconstruction
3D Vision and Multi-View Geometry - AnalysisAdvancedNew
Compare Stereo Depth Methods for a Drone Inspection Startup
You receive 500 calibrated stereo pairs from a turbine inspection plus sparse LiDAR ground truth on each pair. Implement (or wrap) three depth estimators: OpenCV Semi-Global Mat…
- Stereo Depth Estimation
- Multi View Geometry
- Model Evaluation
3D Vision and Multi-View Geometry - AnalysisAdvancedNew
Detect Defects on a Production Line for a Tier-1 Auto Supplier
You receive 12,000 labelled grayscale part images (8,000 good, 4,000 defective across 6 defect types) at 2048x2048. Build a pipeline that does classical preprocessing (illuminat…
- Defect Detection
- Image Classification
- Image Preprocessing
Image Processing and Computational Imaging Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- CodeAdvancedNew
3D Reconstruction of Cultural Artifacts from Photo Sets
Use COLMAP (open-source SfM) + OpenMVS (open-source MVS) on a curated dataset of 5 small artifacts plus a calibration cube. Build a single Python CLI that ingests a folder of im…
- Structure From Motion
- Multi View Stereo
- 3d Reconstruction
Computer Vision - CodeAdvancedNew
Restore Smartphone Low-Light Photos for a Consumer AI App
You receive 200 paired low-light / well-lit phone photos plus 1,000 unpaired low-light photos. Build a pipeline that combines a learned denoiser (e.g. a small DnCNN-style model …
- Image Restoration
- Denoising
- Tone Mapping
Image Processing and Computational Imaging - AnalysisAdvancedNew
Benchmark Visual SLAM Stacks for an Indoor Delivery Robot
You receive 8 indoor rosbag recordings (about 90 minutes total) captured by the robot's stereo camera + Inertial Measurement Unit (IMU) plus ground-truth trajectories from an ex…
- Visual Slam
- Sensor Fusion
- Trajectory Evaluation
Robot Perception and Autonomy - CodeAdvancedNew
Prototype a Computer-Vision QA Tool for a Robotics Manufacturer
As a 4-person team, build: (1) a labeling pipeline on around 2,000 component images (Label Studio is fine); (2) a transfer-learned classifier or a small segmentation model that …
- Computer Vision
- Transfer Learning
- Model Deployment
AI Software Engineering Group Project - Browse challenges
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Product Manager
Ship product that solves real user problems. Combine user research, prototyping, and stakeholder alignment to turn ambiguous briefs into measurable wins — the role at the centre of modern software teams.
- CodeAdvancedNew
Scene-Graph Generation for Retail Shelf Audits
You receive 1,500 labeled shelf photos (anonymized product crops, bounding boxes, and ~12 relation types). Build a pipeline that, for a new shelf photo, outputs (a) detected pro…
- Scene Graph Generation
- Object Detection
- Relation Prediction
Visual Intelligence and Visual Reasoning - CodeAdvancedNew
Multi-View Pose Estimation for a Sports-Analytics Startup
Use the publicly-released SoccerNet or a synthetic 4-view dataset (you can render with Unity or use a provided one). Implement a 2D pose estimator per view (HRNet or YOLOv8-pose…
- Pose Estimation
- Multi View Geometry
- 3d Reconstruction
Computer Vision - CodeAdvancedNew
Multi-Sensor Late-Fusion Prototype for an Indoor AGV
Use the public KITTI dataset (or a similar paired LiDAR+RGB dataset) restricted to static-obstacle classes. Implement a late-fusion baseline: a LiDAR-only detector (PointPillars…
- Sensor Fusion
- 3d Object Detection
- Perception
AI for Autonomous Vehicles - CodeAdvancedNew
Lane-Change Intent Classifier from Dashcam Video
Use a public driving video dataset (e.g., Argoverse 2 sensor or BDD100K) and curate ~6,000 short clips labeled with the three-class intent. Train a temporal model (e.g., a small…
- Video Understanding
- Temporal Modeling
- Model Evaluation
Visual Intelligence and Visual Reasoning Build a verifiable portfolio.
Submissions become evidence. Reviewers with shipping experience score against a rubric; the result becomes a credential anyone can verify.
Why Ewance
- CodeAdvancedNew
Train an Object Detector for an Autonomous-Forklift Robotics Startup
You receive 12,000 labeled warehouse images (pallets, pedestrians, forklifts) plus a 1,500-image safety-test set heavy on pedestrian edge cases. Train an object detector (YOLOv8…
- Object Detection
- Yolo
- Edge Deployment
Deep Learning for Computer Vision
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From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.
Skills and disciplines shown on this page are derived from the Ewance challenge catalogue. When the median annual salary is available for this role via Adzuna, it will be shown above with the sample size and country.