Robust Multi-Human Pose Estimation

@quan9824

With my profile boasting a 100% job completion rate delivered on time, it's clear that I value professionalism and effective communication. As an experienced full-stack developer, I have honed my skills in cutting-edge AI technologies, particularly applying machine learning, deep learning, and computer vision to solve complex problems. Combining my natural language processing skill with object detection tracking and counting positions me as the perfect match for your need in creating an occlusion-aware pose estimation model. Over the years, I have developed a particular interest in using large scale transformer backbones like Mamba/hybrid Transformer models for human pose estimations. This aligns perfectly with your project focus and desired result. To ensure reproducibility on a single GPU, frameworks such as PyTorch, TensorFlow, Detectron2 or MMPose are well within my skillset. Moreover, on projects of this stature, being able to deliver results in both programming code and written form is crucial. My knack for clear technical reporting is backed by my aptitude for concise yet comprehensive structures and my proficiency with drafting well-detailed articles. The bonus? The entire project will be created using 100% open source dependencies- no paid libraries or closed models needed! Choose me to excel your project beyond expectations!

@kamran2012

Interesting project, I will build an occlusion-aware multi-human pose estimation pipeline using a Mamba/Transformer hybrid backbone with part-affinity refinement and kinematic graph constraints — trained and benchmarked on CrowdPose and COCO. Deliverables will include full source code, training scripts, pre-trained weights, and a structured tech report with ablations. For handling severe occlusion, I will integrate graph-based joint dependency modeling so the network infers hidden joints from visible kinematic neighbors rather than guessing independently — this tends to push AP significantly on 30%+ occluded splits. Questions: 1) What is your current baseline model and AP score on the occluded split? 2) Do you need multi-scale inference, or is single-scale acceptable for the 8 FPS target? 3) Should the article follow a specific conference format (e.g., CVPR, ECCV)? Ready to start whenever you are. Kamran

@hotanloc

? fixed price 300$ && timline 3 days I can build a human pose estimation model that works well in crowded images with occluded or partially visible people. I will use a Transformer-based model with geometric priors to detect all joints accurately. Deliverables: Working model with code and training scripts Pre-trained weights with instructions to reproduce results Short report with results and comparisons I will use open-source frameworks (PyTorch, MMPose) and public datasets like CrowdPose or COCO. The model will be fast (≥8 FPS on RTX 3090) and improve over your current baseline. Thanks, Loc

@sf264

Hello, I can develop a research oriented model that will accurately recover every joint in crowded, static images where people overlap, hide behind objects, or appear only partially. Please message me to discuss more details. Looking forward to working with you, Fahad.

@techsty2014

Hi there, I will build an occlusion-aware multi-person pose estimation model using a Mamba-Transformer hybrid backbone with geometric priors — part-affinity refinements and kinematic graph constraints — trained and evaluated on CrowdPose and COCO. I will deliver the full source code, training scripts, pre-trained weights, a reproducible single-GPU pipeline, and a structured research article with ablations and baseline comparisons. For the occlusion handling, I will integrate a visibility-aware attention mechanism that re-weights joint predictions based on occlusion likelihood estimated from the part-affinity maps. This focuses the model's capacity on the joints that actually need hallucination rather than treating all keypoints equally, which is where most baselines lose AP on heavily occluded subjects. Questions: 1) What is your current baseline model and its AP on the occluded test split — so I can target the improvement margin precisely? 2) Do you have a preferred venue or formatting style for the research article (e.g., CVPR, ECCV, or internal report)? Looking forward to your response. Best regards, Kamran

@AhmadXpert2410

Hi there, I can develop a research-oriented, occlusion-aware human pose estimation model that leverages large Transformer backbones combined with geometric priors like part-affinity fields and kinematic graph constraints. Using PyTorch or MMPose, I will design a fully reproducible pipeline on a single GPU that can robustly detect joints even in crowded or partially occluded scenes, ensuring distribution-robust performance under severe occlusion. The deliverables will include source code with training scripts, pre-trained weights, and a detailed read-me for end-to-end reproduction. I will also provide a concise technical report documenting architecture choices, training schedule, evaluation metrics, and ablation studies, along with a structured article comparing results to your baseline. The focus will be on maximizing AP on occluded joints while maintaining inference speed ≥ 8 FPS on an RTX 3090. By combining Transformer-based feature extraction with geometric constraints, the model will handle overlapping people and hidden joints more effectively than standard methods. All dependencies will be open-source, ensuring reproducibility and flexibility for further research and deployment. Regards, Ahmad

@huonghy89

Hi, I hope you are doing well. Very happy to bid your project because my skills are fitted in your project. I have strong experience in computer vision and deep learning, particularly in human pose estimation using Transformer-based and hybrid architectures with PyTorch and MMPose. I have worked on occlusion-robust models, leveraging geometric constraints and large-scale datasets like COCO and CrowdPose for research-grade results. I will design and implement an occlusion-aware pose estimation model using a hybrid Transformer/Mamba-style backbone enhanced with kinematic graph constraints and part-affinity refinements. I will train and evaluate the model on datasets such as CrowdPose and COCO, optimizing for robustness under heavy occlusion while meeting your FPS and AP targets on RTX 3090. I will deliver fully reproducible code, pretrained weights, detailed documentation, and a structured technical report with ablation studies and comparisons. If you send the message, we can discuss the project more. Thanks.

@jeanpatrickr8

Hello, I’m excited about the opportunity to develop a research-oriented model for human pose estimation that addresses the challenges of occlusion and crowd density in static images. I understand your goal is to create a robust solution that leverages large Transformer backbones while ensuring reproducibility and performance. With extensive experience in deep learning and computer vision, I have successfully developed similar models using frameworks like PyTorch and TensorFlow. My expertise includes integrating geometric priors and refining part-affinity to improve accuracy in complex scenarios. To achieve your project goals, I propose the following approach: - Utilize a hybrid Transformer architecture to enhance pose estimation under severe occlusion. - Implement kinematic graph constraints to improve joint recovery in crowded settings. - Ensure the entire pipeline is reproducible on a single GPU, providing clear training scripts and documentation. - Deliver a concise technical report and a structured article comparing results against your baseline. I am eager to collaborate and confident in my ability to meet your requirements, including achieving the specified AP boost and inference speed. Please feel free to reach out so we can discuss the details further and get started immediately.

@qualityxenter

Affordable, Early Delivery. ★★★★★★★★★★★★★★I hold a Masters degree which gives me the requisite background to handle writing from various subjects. I am a highly committed person towards my work. You can rely on QualityXenter for quality and consistency in writing. We never violate copyright rules. I have vast amount of experience in this industry since I am working from 2015 as a professional writer. I provide many modifications till to get your satisfactions. I have access to enough journals to use in your research project. I always produce quality work at VERY LOW RATES so, don't worry if you have a low budget for your work, I will be very happy to make a new client like you. I am producing quality work for my clients including ARTICLE WRITING, REPORT WRITING, ESSAY WRITING, RESEARCH PAPERS, BUSINESS PLAN, TECHNICAL WRITING, MATLAB, THESIS, ACCOUNTING & FINANCE work ETC. Go through my profile link https://www.freelancer.com/u/qualityxenter

@krisk63

Hi there, I'm Kristopher Kramer from McKinney, Texas. I’ve worked on similar projects before, and as a senior full-stack and AI engineer, I have the proven experience needed to deliver this successfully, so I have strong experience in Research and Development, Image Processing, Software Development, Open Source, Computer Vision, Technical Documentation, Machine Learning (ML) and Deep Learning. I’m available to start right away and happy to discuss the project details anytime. Looking forward to speaking with you soon. Best regards, Kristopher Kramer

@durgesh8527

With an eye towards delivering effective solutions tailored to your needs, I am excited to propose my 12+ years of professional experience in Software Development for your Multi-Human Pose Estimation project. I have a proven track record of developing advanced and scalable models, which aligns perfectly with what you’re looking for. Notably, I bring expertise in several in-demand frameworks such as PyTorch, TensorFlow, Detectron2, and MMPose. Pairing this technical know-how with my skillfulness in using large Transformer backbones with geometric priors, I can ensure robust performance even under severe occlusion. I am also well-versed in generating training scripts and delivering concise technical reports that document every step of the process. Moreover, my fluency in popular programming languages like Python and proficiency in using numerous open-source datasets including COCO can prove instrumental throughout the project lifecycle. My commitment to maintaining 100% reliance on open-source dependencies is aligned with your acceptance criteria as well. Together, we can bring your vision to life while adhering strictly to your timeline and expectations. Let's discuss how we can move forward!

@ivicab6

Coming from a background of 6+ years as a full-stack engineer, I bring to the table an outstanding combination of skills that uniquely qualify me for your Robust Multi-Human Pose Estimation project. My expertise in Machine Learning (ML) has been honed through extensive hands-on experience building and shipping production web applications, end-to-end. I have a profound appreciation for clean and maintainable architectures, as well as, optimum performance and reliability - all qualities that I plan to impart in the development process of your project. Moreover, my problem-solving skills have been tested time and again over the years, and I am confident that together we can successfully tackle any challenge this-task throws our way. I have an innate ability to streamline business processes through automation and system-to-system workflows. This knack for reducing manual labor and operational errors will come particularly handy in optimizing your pipeline to achieve reproducible results while ensuring no dependencies on paid libraries or closed models. In conclusion, my unique blend of ML knowledge with practical engineering approaches promises a comprehensive and innovative solution that aligns seamlessly with your requirement of a robustly-performing occlusion-aware human pose estimation model. And it would be my privilege to join you on this endeavor towards a more accurate and efficient model. Let's transform this vision into reality together!

@chrisa207

Hello, As a seasoned developer with a unique blend of AI and full-stack expertise, I'm uniquely positioned to tackle your complex project on robust multi-human pose estimation. My extensive abilities in popular frameworks such as PyTorch, TensorFlow, Detectron2, for instance, align perfectly with the reproducibility you seek. Combine this with my deep experience creating intricate systems that encompass complex workflows, custom APIs, and third-party services, and I'm confident in my capacity to deliver the exacting specifications you need. Not only do I satisfy your openness clause with my 100% reliance on open-source dependencies, but I also draw strength from existing datasets such as CrowedPose and COCO. This complementary approach reduces development time while still ensuring result depth and solidity. Moving onto the deliverables front, my meticulous nature means that documentation is always a top priority for me. Not only will I provide the source code and training scripts but also pre-trained weights with detailed instructions on how to reproduce results end-to-end. Accompanying this will be a comprehensive tech report illustrating architecture choices and metrics, as well as a persuasive article analyzing the results and comparisons. Moreover, my automation-first mindset resonates perfectly with your requirement for an occlusion-aware pose estimation model with improved performance under severe occlusion. This means that n Thanks!

@haseebsidd07

Hey , I just finished reading the job description and I see you are looking for someone experienced in Research and Development, Software Development, Deep Learning, Technical Documentation, Open Source, Image Processing, Computer Vision and Machine Learning (ML). This is something I can do. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? 1. I have done more than 250 major projects. 2. I have not received a single bad feedback since the last 5-6 years. 3. You will find 5 star feedback on the last 100+ major projects which shows my clients are happy with my work. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) I will share with you my recent work in the private chat due to privacy concerns! Please start the chat to discuss it further. Regards, Haseeb,

@edwinv29

Hello, Thank you for the opportunity to submit this bid for your project. I have carefully reviewed the project’s scope and am excited to present my proposal. In past work, I built occlusion-robust pose models that reliably recover all joints in crowded and partially visible scenarios, delivering improved accuracy under severe occlusion. My plan: ✓ Propose a scalable architecture that combines a large Transformer backbone with geometric priors (e.g., part-affinity refinements and kinodynamic graph constraints) for robust joint recovery. ✓ Implement a fully reproducible PyTorch-based pipeline (training scripts, configs) that runs on a single RTX-class GPU with clear setup docs. ✓ Provide pre-trained weights, a concise read-me, and a detailed ablation study plus a short technical report outlining architecture choices, training schedule, and metrics. What is the most important occlusion scenario (e.g., heavy overlap, occlusion by objects, partial visibility) you want to optimize for first, to tailor the initial baseline and evaluation protocol? Please I would love to discuss this project further and answer any questions you may have. Best regards, Edwin

@letswork92

I understand that your primary challenge is developing a robust multi-human pose estimation model capable of accurately identifying joints in crowded settings, particularly when occlusions occur. Achieving this requires sophisticated methodologies that utilize large Transformer backbones combined with geometric priors, which I have extensive experience in. With over 12 years of expertise in machine learning frameworks like PyTorch and TensorFlow, along with knowledge of Detectron2 and MMPose, I can create an effective pipeline that ensures reproducibility on a single GPU. My approach will include delivering an occlusion-aware pose estimation model complete with source code, training scripts, pre-trained weights, and comprehensive documentation to ensure clarity throughout the process. To meet your performance expectations, I’ll focus on achieving an AP boost over your current baseline while maintaining inference speed requirements. Could you share more about the specific metrics you're currently using to evaluate your baseline model? This will help tailor the solution more closely to your needs.

@MIndlabsAi6

Hello, I am Vishal Maharaj, a seasoned Software Development and Computer Vision expert with 20 years of experience. I have carefully reviewed the requirements for the project and am confident in my ability to deliver a robust multi-human pose estimation model. My proposed solution involves leveraging large Transformer backbones combined with geometric priors for accurate joint recovery in crowded and occluded images. I plan to use frameworks like PyTorch or TensorFlow to ensure reproducibility on a single GPU. The deliverables will include an occlusion-aware pose estimation model with training scripts, pre-trained weights, a detailed tech report, and a structured article with results and comparisons. I would be happy to discuss this project further. Please feel free to initiate a chat. Cheers, Vishal Maharaj

@daxm0

Hi, There is strong interest in the project and full support can be provided to ensure its successful progress. I have a clear understanding of your main objectives. I’ve carefully reviewed the requirements to ensure nothing is overlooked. I will deliver a final result that aligns perfectly with your expectations. As a Senior Software Engineer, I bring extensive experience in Software Development, Machine Learning (ML) and technical assessment. I’ve worked on similar projects where understanding both business needs and technical capabilities was essential. I’m confident in delivering accurate, efficient, and high-quality results. I have a few questions before we get started. Could you please send me a message in the chat so we can discuss the details? Thanks, Dax Manning

@Kashifscode

As a skilled software developer, my expertise is not limited to just one domain. Although my background may not scream Pose Estimation, I am confident that my understanding and application of complex algorithms along with my well-honed skills in Python, Deep Learning Frameworks such as TensorFlow and PyTorch will enable me to tackle this project with precision. In conclusion, while I may not have an explicit history of working in the Computer Vision field specifically for Pose Estimation models, my broader skill set - including technical documentations - prove that I am adaptable and can certainly bring valuable insights to the table. As you entrust this project to me, rest assured that I will go above and beyond to meet all of your expectations; delivering impeccable results on metrics like AP boost, inference speed and full adherence to open-source dependencies. Let's transform this opportunity into a successful collaboration!