This position requires highly-motivated individuals who want to join us in the fast-moving field of large-scale models for human-centric 3D representations. You will be responsible for developing implementing evaluating and improving computer vision and GenAI algorithms that model photorealistic humans in complex and diverse internship areas:* Human-centric video diffusion models* 3D reconstruction of humans* Human-centric generative models* Face and body tracking* Human-object Interaction* Advanced neural rendering techniques* Neural simulation techniques* Power-efficient deep learning
- Strong understanding of modern machine learning techniques (e.g. generative multi-modal and foundational models video understanding and self-supervised learning).
- Strong understanding of modern approaches for 3D reconstruction and rendering (e.g. MVS NeRF Gaussian Splatting).
- Fluency in Python and Machine Learning frameworks (e.g. PyTorch) is required.
- Excellent communication and collaboration skills.
- Good problem solving and analytical thinking abilities.
- Working towards a MSc or PhD degree in Computer Science or a related field. PhD students are preferred for research-focused internships.
- At the end of the internship you must return to university to continue your education or the internship must be the last requirement for you to graduate.
- Hands-on experience with image or video diffusion models 3D generative models Gaussian splatting or vision foundation models.
- Hands-on experience with human modeling algorithms (e.g. skeletal tracking body shape and pose models hair and garment modeling).
- Publication record at top conferences such as CVPR ECCV ICCV NeurIPS or SIGGRAPH is a plus.
- Availability for 6 months minimum is preferred.
- Industry experience is a plus.
Required Experience:
Intern
This position requires highly-motivated individuals who want to join us in the fast-moving field of large-scale models for human-centric 3D representations. You will be responsible for developing implementing evaluating and improving computer vision and GenAI algorithms that model photorealistic hum...
This position requires highly-motivated individuals who want to join us in the fast-moving field of large-scale models for human-centric 3D representations. You will be responsible for developing implementing evaluating and improving computer vision and GenAI algorithms that model photorealistic humans in complex and diverse internship areas:* Human-centric video diffusion models* 3D reconstruction of humans* Human-centric generative models* Face and body tracking* Human-object Interaction* Advanced neural rendering techniques* Neural simulation techniques* Power-efficient deep learning
- Strong understanding of modern machine learning techniques (e.g. generative multi-modal and foundational models video understanding and self-supervised learning).
- Strong understanding of modern approaches for 3D reconstruction and rendering (e.g. MVS NeRF Gaussian Splatting).
- Fluency in Python and Machine Learning frameworks (e.g. PyTorch) is required.
- Excellent communication and collaboration skills.
- Good problem solving and analytical thinking abilities.
- Working towards a MSc or PhD degree in Computer Science or a related field. PhD students are preferred for research-focused internships.
- At the end of the internship you must return to university to continue your education or the internship must be the last requirement for you to graduate.
- Hands-on experience with image or video diffusion models 3D generative models Gaussian splatting or vision foundation models.
- Hands-on experience with human modeling algorithms (e.g. skeletal tracking body shape and pose models hair and garment modeling).
- Publication record at top conferences such as CVPR ECCV ICCV NeurIPS or SIGGRAPH is a plus.
- Availability for 6 months minimum is preferred.
- Industry experience is a plus.
Required Experience:
Intern
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