美图3D Vision Algorithm Intern (3D Human Reconstruction & Tracking)
任职要求
Experience · PhD candidate in Computer Science, Artificial Intelligence, Intelligent Arts, or related fields · Proficient in Python, with experience using common libraries (e.g., NumPy, Transformers, Diffusers, Open3D), and strong hands-on experience with deep learning frameworks such as PyTorch · Strong, sustained interest in image/video aesthetics or 3D art; resilient mindset and openness to change Skills & Abilities · Solid engineering implementation skills and rigorous experimental practices; able to independently complete module-level tasks · Proficient with AI-assisted programming tools; maintains clean, well-structured code · Strong ability to read, analyse, summarize, and reproduce academic papers · Clear logical thinking, strong problem-decomposition skills, and curiosity about underlying principles Motivation & Values · Long-term interest in AI + imaging / 3D / aesthetics · Proactive, self-driven, and willing to explore new approaches and challenges · Alignment with a product culture centred on user experience and technical value Bonus Points · Prior experience with SMPL, human pose estimation, 3D reconstruction, or tracking · Familiarity with video understanding, diffusion models, autoregressive models, or flow-matching methods · Research projects, comp…
工作职责
Location & Duration Sydney Central; 6-12 months Role Overview You will participate in the research and development of human aesthetic enhancement and spatiotemporally consistent editing technologies at Meitu. You will work directly with real, product-scale datasets and state-of-the-art algorithms. Depending on the internship track, your work may include (but is not limited to): · Fine-grained and controllable image / video aesthetic enhancement · 2D / 3D human tracking and 3D reconstruction · Regression, reconstruction, and structural constraints of digital human models (e.g., SMPL) This role offers the opportunity to produce both production-ready technical outcomes and high-quality academic research results. It is a research-and-engineering-oriented internship, ideal for candidates with strong interest and capability in 3D vision fundamentals, human visual quality enhancement, video generation models, and 3D human modelling. Key Responsibilities · Research and implement algorithms related to depth estimation, multi-view generation, and 2D / 3D tracking with spatiotemporal reconstruction · Follow state-of-the-art 3D vision papers and open-source projects; reproduce experiments and adapt methods to practical applications · Collaborate with data teams to refine the 3D aesthetic development pipeline, improve data collection and quality evaluation, and establish foundations for high-quality scaling · Explore the integration of human structure priors (Skeleton / SMPL / Mesh) with multi-modal cues such as depth, normals, and optical flow in reconstruction and generative models · Assist in building data processing, evaluation, and visualization tools (e.g., immersive video aesthetic editing) to support rapid iteration · Enable high-quality projection of 3D features into 2D visual outputs, with the goal of producing A-level or above academic publications
About the Team We are a visual R&D team focused on human aesthetic modelling and advanced 3D vision research. Our work spans human image understanding, 3D reconstruction, and intelligent aesthetic enhancement. By combining academic research methodologies with real-world product deployment, we continuously explore new frontiers in AI-driven image/video generation, editing, spatiotemporal consistency, and 3D structural understanding. Location & Duration Sydney Central; 6-12 months Role Overview You will participate in the research and development of human aesthetic enhancement and spatiotemporally consistent editing technologies at Meitu. You will work directly with real, product-scale datasets and state-of-the-art algorithms. Depending on the internship track, your work may include (but is not limited to): · Fine-grained and controllable image / video aesthetic enhancement · 2D / 3D human tracking and 3D reconstruction · Regression, reconstruction, and structural constraints of digital human models (e.g., SMPL) This role offers the opportunity to produce both production-ready technical outcomes and high-quality academic research results. It is a research-and-engineering-oriented internship, ideal for candidates with strong interest and capability in 3D vision fundamentals, human visual quality enhancement, video generation models, and 3D human modelling. Key Responsibilities · Research and implement algorithms related to depth estimation, multi-view generation, and 2D / 3D tracking with spatiotemporal reconstruction · Follow state-of-the-art 3D vision papers and open-source projects; reproduce experiments and adapt methods to practical applications · Collaborate with data teams to refine the 3D aesthetic development pipeline, improve data collection and quality evaluation, and establish foundations for high-quality scaling · Explore the integration of human structure priors (Skeleton / SMPL / Mesh) with multi-modal cues such as depth, normals, and optical flow in reconstruction and generative models · Assist in building data processing, evaluation, and visualization tools (e.g., immersive video aesthetic editing) to support rapid iteration · Enable high-quality projection of 3D features into 2D visual outputs, with the goal of producing A-level or above academic publications
The NVIDIA Isaac Loco-Manipulation team is seeking exceptional machine learning Interns to join our world-class robotics initiatives. As an intern, you’ll work alongside industry-leading experts, gaining hands-on experience and contributing to the future of humanoid loco-manipulation. We’re looking for strategic, ambitious, and creative individuals who are passionate about pushing the boundaries of robotics. What You’ll Be Doing: • Collaborate with researchers and engineers to define and execute projects focused on humanoid loco-manipulation and mobile manipulation. • Contribute to GR00T and Cosmos foundation models. • Support the development of reference workflows in Isaac Lab and Newton. • Advance technologies for robot learning and synthetic data generation using human video datasets. • Design, implement, and deploy novel algorithms for humanoid robot locomotion and manipulation in both simulated and real-world environments. • Integrate your work with NVIDIA’s advanced robotics platforms. • Transfer your innovations into products, with deliverables including prototypes, patents, and/or publications in top conferences and journals.
Summary of the position This position in the Camera Engineering Team will focus on new camera tests and image quality by a variety of new technologies and lab automation. The engineer will be responsible for the design, development, and optimization of image processing and computer vision algorithms, including image enhancement, object detection, tracking, image quality tool development, participate in the integration of machine learning models (e.g., deep learning-based image recognition), and conduct algorithm testing, debugging, and performance evaluation to ensure the image quality of Tesla’s camera systems. This role involves collaboration with designers, engineering, manufacturing and requires the ability to distill highly technical information and effectively communicate with other teams and management. Minimum