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Google just revealed an ABSOLUTE depth estimation model 🤯 As opposed to recent depth models (Marigold, PatchFusion) which aim for maximum details, DMD aims to estimate the ABSOLUTE depth (in meters) within the image More details below ⬇️⬇️

Alex Carlier

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199,532 просмотров • 2 лет назад •via X (Twitter)

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PatchFusion was just released. Compared to ZoeDepth, it predicts depth maps with much finer details, just look at the comparison below! 🤯 Its main contribution is a new Global-to-Local module and Consistency-Aware Training. More examples below (with code) ⬇️⬇️

PatchFusion was just released. Compared to ZoeDepth, it predicts depth maps with much finer details, just look at the comparison below! 🤯 Its main contribution is a new Global-to-Local module and Consistency-Aware Training. More examples below (with code) ⬇️⬇️

Alex Carlier

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Depth Any Video with Scalable Synthetic Data AI physicists and chemists continue to make strides in depth estimation from video. Check out this new paper featuring some impressive examples. See the thread for more details (unfortunately no code yet). Abstract: Video depth estimation has long been hindered by the scarcity of consistent and scalable ground truth data, leading to inconsistent and unreliable results. In this paper, we introduce Depth Any Video, a model that tackles the challenge through two key innovations. First, we develop a scalable synthetic data pipeline, capturing real-time video depth data from diverse game environments, yielding 40,000 video clips of 5-second duration, each with precise depth annotations. Second, we leverage the powerful priors of generative video diffusion models to handle real-world videos effectively, integrating advanced techniques such as rotary position encoding and flow matching to further enhance flexibility and efficiency. Unlike previous models, which are limited to fixed-length video sequences, our approach introduces a novel mixed-duration training strategy that handles videos of varying lengths and performs robustly across different frame rates 0 - even on single frames. At inference, we propose a depth interpolation method that enables our model to infer high-resolution video depth across sequences of up to 150 frames. Our model outperforms all previous generative depth models in terms of spatial accuracy and temporal consistency.

Depth Any Video with Scalable Synthetic Data AI physicists and chemists continue to make strides in depth estimation from video. Check out this new paper featuring some impressive examples. See the thread for more details (unfortunately no code yet). Abstract: Video depth estimation has long been hindered by the scarcity of consistent and scalable ground truth data, leading to inconsistent and unreliable results. In this paper, we introduce Depth Any Video, a model that tackles the challenge through two key innovations. First, we develop a scalable synthetic data pipeline, capturing real-time video depth data from diverse game environments, yielding 40,000 video clips of 5-second duration, each with precise depth annotations. Second, we leverage the powerful priors of generative video diffusion models to handle real-world videos effectively, integrating advanced techniques such as rotary position encoding and flow matching to further enhance flexibility and efficiency. Unlike previous models, which are limited to fixed-length video sequences, our approach introduces a novel mixed-duration training strategy that handles videos of varying lengths and performs robustly across different frame rates 0 - even on single frames. At inference, we propose a depth interpolation method that enables our model to infer high-resolution video depth across sequences of up to 150 frames. Our model outperforms all previous generative depth models in terms of spatial accuracy and temporal consistency.

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Introducing 🛹 RollingDepth 🛹 — a universal monocular depth estimator for arbitrarily long videos! Our paper, “Video Depth without Video Models,” delivers exactly that, setting new standards in temporal consistency. Check out more details in the thread 🧵

Introducing 🛹 RollingDepth 🛹 — a universal monocular depth estimator for arbitrarily long videos! Our paper, “Video Depth without Video Models,” delivers exactly that, setting new standards in temporal consistency. Check out more details in the thread 🧵

Anton Obukhov

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A close-up only works when depth feels real. In this shot, we pushed blur and shading to shape the depth of field (DoF), not just for realism, but to deepen the emotion within the frame. Produced by Otsu Labs & Studio Munbou

A close-up only works when depth feels real. In this shot, we pushed blur and shading to shape the depth of field (DoF), not just for realism, but to deepen the emotion within the frame. Produced by Otsu Labs & Studio Munbou

Otsu Labs

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It's also important to verify the token To safeguard against scams, rug pulls, and honeypots, it’s essential to confirm the token's contract Just enter the contract address to access in-depth details about the token’s security:

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Scientists at University of Western Australia set new record for deepest fish ever filmed at a depth of 8,336 meters. During an expedition that took place in August 2022, the research vessel DSSV Pressure Drop embarked on a two-month journey to investigate trenches in the Pacific Ocean near Japan. The primary objective of the expedition was to examine the populations of deep-sea fish. While conducting filming activities, the research team unexpectedly encountered a previously unknown species of snailfish at an astounding depth of 8,336 meters, equivalent to over 27,000 feet, specifically in the Izu-Ogasawara Trench. At a depth of 8,022 meters, scientists successfully obtained two fish from traps. This achievement is noteworthy because it includes the capture of a snailfish species known as Pseudoliparis belyaevi. Notably, this is the first time a fish has been collected from depths exceeding 8,000 meters, as these snailfish were previously observed solely at a shallower depth of 7,703 meters.

Scientists at University of Western Australia set new record for deepest fish ever filmed at a depth of 8,336 meters. During an expedition that took place in August 2022, the research vessel DSSV Pressure Drop embarked on a two-month journey to investigate trenches in the Pacific Ocean near Japan. The primary objective of the expedition was to examine the populations of deep-sea fish. While conducting filming activities, the research team unexpectedly encountered a previously unknown species of snailfish at an astounding depth of 8,336 meters, equivalent to over 27,000 feet, specifically in the Izu-Ogasawara Trench. At a depth of 8,022 meters, scientists successfully obtained two fish from traps. This achievement is noteworthy because it includes the capture of a snailfish species known as Pseudoliparis belyaevi. Notably, this is the first time a fish has been collected from depths exceeding 8,000 meters, as these snailfish were previously observed solely at a shallower depth of 7,703 meters.

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Upscale-A-Video was just released and it's so good! 🤯 It's a temporal-consistent Diffusion Model for video Super-Resolution, and has some of the best results I've ever seen, look at how sharp those lines become! More details below ⬇️⬇️

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I did this test render earlier as i realized its a nice behind the scenes way to see the full volume and depth of the models and gas clouds. I thought in the future i might make more of these as Supporter exclusive little bonuses for renders i made. what do you all think?

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