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 ⬇️⬇️show more

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) ⬇️⬇️show more

🤔Applying Depth Estimation models directly to videos can result... in inconsistency between frames. 💪Well, not anymore. 🔥ChronoDepth is a new approach to video depth estimation that focuses on achieving both accuracy within each frame and consistency across frames. 📜More👇show more

Some tweaks to the details to enhance depth. #Live2D #Live2DWIP

Discover the right 3D Geometric Foundation Model for your... task—whether it’s stereo matching, multi-view depth estimation, video depth, pose estimation, semantic understanding, or novel view synthesis. Explore more insights in our #E3DBench #FoundationModel #3D #GaussianSplatting. Project Webpage:show more

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.show more

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 🧵show more

An image + a detailed normal map generated by... GeoWizard --> a relightable image. Geowizard is a generative geometry estimation model that could jointly produce high-quality depth and normal with intricate details. Try our huggingface demo here: #huggingface #gradio #geowizardshow more

Spent some time this week playing with depth estimation... models. Monocular depth estimation has come a long way, but in terms of metric accuracy and geometric consistency, stereo depth still has it beat by a wide margin. DepthPro (mono) vs FoundationStereo (stereo)show more

Video diffusion models are just overqualified depth estimators! Deterministic... single-pass depth estimation based on WanV2.1. - SOTA 5.5 AbsRel on ScanNet - data-efficient than baselines; - no temporal flicker + infinite-length estimation w/ zero scale drift.show more

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 Munboushow more

Doesn't look like the super low-res depth maps from... the iPhone Pro's LiDAR sensor would be too useful as supervision (or sanity check) for recent monocular depth estimators.show more

Calculating pothole volume from a 2D image is challenging... but possible: > Assign each pothole an ID to avoid duplication. > Use basic trigonometry to convert pixels to real-world meters. > Apply a novel algorithm to estimate depth using road engineering data.show more

Introducing ⇆ Marigold-DC — our training-free zero-shot approach to... monocular Depth Completion with guided diffusion! If you have ever wondered how else a long denoising diffusion schedule can be useful, we have an answer for you! Details 🧵show more

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:show more

Here's a comparison of Depth Pro [arXiv:2410.02073], Marigold-E2E [arXiv:2409.11355],... and Metric3D v2 [arXiv:2404.15506]. Looks like Marigold is attempting to look through the glass while the two metric models aren't. Dmytro Mishkin 🇺🇦show more

Introducing Depth Estimation with NVIDIA’s FoundationStereo—a new open tutorial... and codebase for metric depth sensing using Project Aria Gen 2 devices. ⚡️ Real-time ready (20 FPS) 🤖 Zero-shot generalization ⚡️Stereo image rectification and disparity estimation 🔓 Open Source Check out the code and tutorial: 🔌Chris Sweeneyshow more

Trying out realtime video-to-depth on an iPhone 15 using... Depth Anything V2.show more

Gave a robot 3D vision with just a regular... camera👁️ Full Tutorial: Deployed #Depth Anything V3​ on NVIDIA Robotics Jetson AGX Orin. It estimates depth from 2D images in real-time—no special sensors needed. Just need #Monocular depth estimation + #TensorRT​ optimization + #ROS2​ integration. 👉 Learn more about reComputer Robotics J5011: #TheAIHardwarePartnershow more

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.show more

gm So if you ask Nano Banana to make... an image into a Depth Map, you get a grayscale image where white=close & black=far Then ask Google AI Studio for an app that turns depth maps into point clouds & lets you control them with hand gestures from webcam blam you’re Tony Starkshow more