Naila Murray, director of AI research at Meta, discusses the latest trends in computer vision, including controllable generation, visual programming, 3D Gaussian splatting, and multimodal models. She shares insights on open source projects like Segment Anything, ControlNet, and DINOv2. Naila also talks about exciting opportunities in the field and predicts future advancements in computer vision.
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Quick takeaways
Finding the balance between memorization and creativity in vision models is an exciting opportunity in computer vision.
The use of simulated data can expand training data and bridge the gap between limited real data and the need for large-scale training in vision models.
Advancements in video generation, multimodality, and embodied models are anticipated in computer vision, enabling immersive multimedia experiences and interactions with the environment.
Deep dives
Balancing Memorization and Creativity in Vision Models
One exciting opportunity in computer vision is finding the balance between memorization and creativity in vision models. This involves exploring how to encode and retrieve knowledge while also allowing for imaginative and creative outputs. This will require research on controlling the knowledge storage and retrieval processes within vision models to enable a combination of factual accuracy and creative generation.
Expanding the Use of Simulated Data
Another exciting opportunity is the use of simulated data as a means to expand the amount of training data available. Improved generative models, such as Gaussian splatting, can be utilized to generate diverse and realistic simulated data for training vision models. Simulated data can augment real-world datasets and help bridge the gap between limited real data and the need for large-scale training.
Advancements in Video Generation and Multimodality
Advancements in video generation and multimodality are expected in the coming years. This includes improving the modeling of motion in videos and synchronizing audio with visual content. The combination of realistic visuals, audio, and motion will enable the creation of immersive and compelling multimedia experiences. Embodied models that take an egocentric perspective are also anticipated to progress, enabling interactions between vision models and the environment.
Milestone Achievements in Robotics and Reinforcement Learning
There is potential for milestone achievements in the integration of vision models with robotics and reinforcement learning. This involves equipping robots with language models and enabling them to interpret and respond to prompts in real-world scenarios. Reinforcement learning techniques can be leveraged to train robots to navigate, perceive, and interact within their environment, leading to advancements in various areas such as autonomous driving and embodied intelligence.
Continued Progress in Open Science and Research Collaboration
Lastly, the vibrant research ecosystem within computer vision will continue to drive progress through open science and collaboration. Researchers will contribute to the development and sharing of open source projects, advancing the field collectively. This collaborative effort will fuel rapid progress and innovation in computer vision, further pushing the boundaries of what is possible.
Today we kick off our AI Trends 2024 series with a conversation with Naila Murray, director of AI research at Meta. In our conversation with Naila, we dig into the latest trends and developments in the realm of computer vision. We explore advancements in the areas of controllable generation, visual programming, 3D Gaussian splatting, and multimodal models, specifically vision plus LLMs. We discuss tools and open source projects, including Segment Anything–a tool for versatile zero-shot image segmentation using simple text prompts clicks, and bounding boxes; ControlNet–which adds conditional control to stable diffusion models; and DINOv2–a visual encoding model enabling object recognition, segmentation, and depth estimation, even in data-scarce scenarios. Finally, Naila shares her view on the most exciting opportunities in the field, as well as her predictions for upcoming years.
The complete show notes for this episode can be found at twimlai.com/go/665.
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