Top 7 Papers Presented by Meta at CVPR 2024
25/06/2024
3:45 pm
Over 11,500 papers were submitted to CVPR 2024, a significant increase from the 9,155 papers submitted last year.
Explore the fascinating world of Computer Vision, where artificial intelligence meets visual perception. Learn how machines interpret and understand images and videos, revolutionising industries from healthcare to autonomous vehicles. Discover key techniques, applications, and breakthroughs in this rapidly evolving field. Uncover how Computer Vision is shaping our future by enabling machines to see and comprehend the world around us.
Over 11,500 papers were submitted to CVPR 2024, a significant increase from the 9,155 papers submitted last year.
Wipro’s VisionEdge platform powers more than 5,000 flight information displays across 15+ airports in the US, Canada, India, and the Middle East.
The AI for humanitarian service, ‘Desk of Goodness’ is available across six Adani airports in India.
Their technology is being used by the United Nations
“I believe that Gen AI and AI is magical, and the impact it has on our lives and society is profound, but the failures are also very detrimental,” said Gaurav Agarwal, founder and CEO of RagaAI
Worldwide, computer vision algorithms are becoming an indispensable tool for law enforcement agencies
AI is the ultimate sidekick for SCM professionals, providing insights and support to help them make better decisions faster.
Organisations and people must take the initiative in utilising computer vision and facial recognition in an ethical and responsible manner until governmental bodies are able to effectively regulate these developing technologies. A fundamental key is to build responsibly and only with the goal to serve the purpose.
YOLO v8 claims to be faster, precise for better object detection, image segmentation and classification.
“Machine learning is breaking things apart and allowing new people to come in. There is now a jump ball where legacy is no longer a strength”– Krishna Rangasayee
Amazon introduced a new intelligent robotic system called ‘Sparrow,’ a SOTA robot that handles millions of diverse products.
RawNeRF’s noise reduction method when combined with the 3D scene gives a high-resolution output which is seamless when transitioning between angle and positions.
Three young innovators of Shiv Nadar School have developed an AI-enabled solution to address the problem of stray dogs’ starvation
According to the team, MT-YOLOv6 has carried out improvements and optimisations at the algorithmic level like training strategies and network structure and has displayed impressive results in terms of accuracy and speed when tested on COCO datasets.
With Timm and Transformers side by side, everyone will benefit from a more direct path from computer vision experimentation to stable, well-documented APIs.
Deploy and demonstrate the capabilities of DL models with Streamlit
GRIT is an evaluation only benchmark for evaluating the performance of vision systems across several image prediction tasks, concepts, and data sources.
Why is there such intense competition in this field, or in other words, are other AI domains lagging behind NLP in terms of innovation?
PyTorchCV helps in building high-performing transfer learning models that have shown better performance than the other existing frameworks.
STEGO nearly doubles in MIoU un both unsupervised as well as linear probe metrics in comparison to its predecessors.
HPCL is deploying AI-based visual analytics across its retail network to improve customer satisfaction and safety.
In this article, we will go through an overview of each of the popular image reconstruction techniques and will understand how these techniques work.
I would recommend people to focus on graph neural networks.
Kubric is an open-source Python framework that allows you to create photo-realistic scenes by combining the functions of PyBullet and Blender.
‘Psyight’ helps identify all Indian fruits and vegetables without using barcodes.
Object detection forms the foundation of many other downstream computer vision tasks, such as image segmentation, image captions, object tracking, and more.
Vision Transformers (ViTs) is emerging as an alternative to convolutional neural networks (CNNs) for visual recognition.
Vision transformer (ViT) is a transformer used in the field of computer vision that works based on the working nature of the transformers used in the field of natural language processing. Internally, the transformer learns by measuring the relationship between input token pairs. In computer vision, we can use the
They have applied it separately to speech, text and images where it outperformed the previous best single-purpose algorithms for computer vision and speech.
In this article, we will discuss the VisionKG in detail and will see how it can query the dataset like COCO and ImageNet.
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In an exclusive interview with AIM, IndiaAI Mission CEO said Sarvam AI and BharatGen will