Abhinav Girdhar’s Post

Check out the new paper, "Improving 2D Feature Representations by 3D-Aware Fine-Tuning." This research introduces a novel approach to enhance 2D feature representations by incorporating 3D-aware fine-tuning, significantly improving the performance of 2D image recognition tasks. The paper provides a detailed analysis of the techniques used, making it a valuable resource for developers and researchers in AI and computer vision. The findings highlight substantial improvements in feature representation and model accuracy. For those interested in the technical aspects and practical applications of 2D and 3D integration, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/gTPJXuvS] #AI #MachineLearning #ComputerVision #DataScience #Research #Innovation #2D3DIntegration #FeatureRepresentation

Check out the new paper, "PartGLEE: A Foundation Model for Recognizing and Parsing Any Objects." This research introduces PartGLEE, a versatile model designed to recognize and parse a wide variety of objects, enhancing the capabilities of object recognition systems. The paper provides a detailed analysis of the techniques used, making it a valuable resource for developers and researchers in AI and computer vision. The findings highlight substantial improvements in object recognition and parsing accuracy. For those interested in the technical aspects and practical applications of object recognition, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/gjazYJuy] #AI #MachineLearning #ComputerVision #DataScience #Research #Innovation #ObjectRecognition #PartGLEE

Check out the new paper, "Matting by Generation." This research introduces an innovative approach to image matting by redefining the task as a generative modeling problem, leveraging diffusion models to produce high-quality mattes with superior resolution and detail. The paper provides a detailed analysis of the techniques used, making it a valuable resource for developers and researchers in AI and computer vision. The findings highlight substantial improvements in image matting accuracy and visual quality. For those interested in the technical aspects and practical applications of image matting, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/gs_-x5pP] #AI #MachineLearning #ImageMatting #DataScience #Research #Innovation #GenerativeModeling #MattingByGeneration

Check out the new paper, "Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation." This research introduces advanced diffusion models that enhance joint trajectory prediction and controllable generation, significantly improving the accuracy and flexibility of predictive modeling. The paper provides a detailed analysis of the techniques used, making it a valuable resource for developers and researchers in AI and machine learning. The findings highlight substantial improvements in trajectory prediction and model control. For those interested in the technical aspects and practical applications of diffusion models, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/ghuvypTb] #AI #MachineLearning #DiffusionModels #DataScience #Research #Innovation #TrajectoryPrediction #ModelControl

Discover the new paper, "DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents." This research introduces DisCo-Diff, a novel approach that integrates discrete latent variables into continuous diffusion models, significantly improving their performance and efficiency. The paper provides a comprehensive analysis of the techniques used, making it a valuable resource for developers and researchers in AI and machine learning. The findings highlight substantial improvements in model accuracy and computational efficiency.For those interested in the technical aspects and practical applications of diffusion models, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/g5Jg7yHR] #AI #MachineLearning #DiffusionModels #DataScience #Research #Innovation #DiscreteLatents #ComputationalEfficiency #DisCoDiff

Are the benchmarks we use to measure AI progress lying to us? Fabian Gröger’s paper from NeurIPS 2024 reveals a hidden crisis in machine learning: our benchmark datasets are contaminated. From medical imaging to computer vision, these datasets contain off-topic samples, duplicates, and label errors that artificially inflate model performance. It's like measuring temperature with a broken thermometer – how can we trust the results? Enter SELFCLEAN, a solution that uses self-supervised learning to automatically detect data quality issues. Unlike traditional approaches, it learns from the data's inherent structure without relying on potentially flawed labels. The researchers tested SELFCLEAN on twelve major datasets and found surprising results: even widely-used benchmarks contain significant contamination that affects model evaluation. This is not only about cleaning data; it involves fundamentally rethinking how we measure AI progress. Want to dive deeper? Check out Harpreet Sahota 🥑's full breakdown in his blog: https://lnkd.in/gcUaEUq9 #computervision #ai #artificialintelligence #machinevision #machinelearning #datascience #neurips2024

Check out the new paper, "CountGD: Multi-Modal Open-World Counting." This research introduces a multi-modal approach for open-world object counting, leveraging text and image data to accurately count objects in diverse and dynamic environments. The paper provides a detailed analysis of the techniques used, making it a valuable resource for developers and researchers in AI and computer vision. The findings highlight significant improvements in the accuracy and flexibility of counting objects in real-world scenarios. For those interested in the technical aspects and practical applications of object counting, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/g5sJYzEH] #AI #MachineLearning #ComputerVision #DataScience #Research #Innovation #ObjectCounting #MultiModal

Check out the new paper, "SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency." This research introduces SV4D, a latent video diffusion model designed to generate novel view videos of dynamic 3D objects with temporal consistency. The paper provides a detailed analysis of the techniques used, making it a valuable resource for developers and researchers in AI and computer vision. The findings highlight substantial improvements in novel-view video synthesis and 4D content generation. For those interested in the technical aspects and practical applications of 3D content generation, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/gdRfTxu9] #AI #MachineLearning #3DContent #DataScience #Research #Innovation #VideoDiffusion #SV4D

Check out the new paper, "Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining." This research introduces Lumina-mGPT, a model designed to generate high-quality photorealistic images from text prompts using advanced multimodal generative pretraining techniques. The paper provides a detailed analysis of the techniques used, making it a valuable resource for developers and researchers in AI and image generation. The findings highlight significant improvements in image quality and generation flexibility. For those interested in the technical aspects and practical applications of text-to-image generation, this paper is essential reading. It offers insights and solutions that contribute meaningfully to advancements in the field. Read the full paper here: [https://lnkd.in/gkaFqJfR] #AI #MachineLearning #ImageGeneration #DataScience #Research #Innovation #TextToImage #LuminaMGPT

Excited to share our research, "Unmasking Deepfakes: A Systematic Review of Deepfake Detection and Generation Techniques using Artificial Intelligence", published in Expert Systems with Applications. In this study, Asst. Prof. Araz Taeihagh and Dr. Fakhar Abbas delve deep into the world of deepfake detection and generation, and explore how cutting-edge AI technologies affect online disinformation. This systematic literature analysis provides insights into automatic detection frameworks, algorithms, and tools for identifying deepfake audio, images, and videos. The paper also highlights practical challenges and offers policy recommendations on how AI can be leveraged to combat disinformation. A must-read for those interested in the intersection of AI and policy! Read more: https://bit.ly/4cXebhH #Deepfakes #AI #Disinformation #Policy #iGYRO #CTIC