Cover Image

Online Video Depth Anything: Temporally-Consistent Depth Prediction with Low Memory Consumption

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Feiden, Johann-Friedrich, Küchler, Tim, Zavadski, Denis, Savchynskyy, Bogdan, Rother, Carsten
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ControlNet-XS: Rethinking the Control of Text-to-Image Diffusion Models as Feedback-Control Systems
by: Zavadski, Denis, et al.
Published: (2023)

PrimeDepth: Efficient Monocular Depth Estimation with a Stable Diffusion Preimage
by: Zavadski, Denis, et al.
Published: (2024)

A Framework for Low-Effort Training Data Generation for Urban Semantic Segmentation
by: Zavadski, Denis, et al.
Published: (2025)

Unsupervised Deep Graph Matching Based on Cycle Consistency
by: Tourani, Siddharth, et al.
Published: (2023)

Product-Quantised Image Representation for High-Quality Image Synthesis
by: Zavadski, Denis, et al.
Published: (2025)

Video Depth Anything: Consistent Depth Estimation for Super-Long Videos
by: Chen, Sili, et al.
Published: (2025)

Relative-Interior Solution for the (Incomplete) Linear Assignment Problem with Applications to the Quadratic Assignment Problem
by: Dlask, Tomáš, et al.
Published: (2023)

EndoStreamDepth: Temporally Consistent Monocular Depth Estimation for Endoscopic Video Streams
by: Li, Hao, et al.
Published: (2025)

Learning Temporally Consistent Video Depth from Video Diffusion Priors
by: Shao, Jiahao, et al.
Published: (2024)

Cycle-Consistent Multi-Graph Matching for Self-Supervised Annotation of C.Elegans
by: Karg, Christoph, et al.
Published: (2025)

Amodal Depth Anything: Amodal Depth Estimation in the Wild
by: Li, Zhenyu, et al.
Published: (2024)

PTC-Depth: Pose-Refined Monocular Depth Estimation with Temporal Consistency
by: Han, Leezy, et al.
Published: (2026)

Depth Anything V2
by: Yang, Lihe, et al.
Published: (2024)

Depth Anything with Any Prior
by: Wang, Zehan, et al.
Published: (2025)

STATIC : Surface Temporal Affine for TIme Consistency in Video Monocular Depth Estimation
by: Yang, Sunghun, et al.
Published: (2024)

DepthSync: Diffusion Guidance-Based Depth Synchronization for Scale- and Geometry-Consistent Video Depth Estimation
by: Dong, Yue-Jiang, et al.
Published: (2025)

Any to Full: Prompting Depth Anything for Depth Completion in One Stage
by: Zhou, Zhiyuan, et al.
Published: (2026)

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth
by: Liu, Yuecheng, et al.
Published: (2026)

Depth-Guided Metric-Aware Temporal Consistency for Monocular Video Human Mesh Recovery
by: Cen, Jiaxin, et al.
Published: (2026)

Surgical Depth Anything: Depth Estimation for Surgical Scenes using Foundation Models
by: Lou, Ange, et al.
Published: (2024)

Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimation
by: Lin, Haotong, et al.
Published: (2024)

MapAnything: Evaluating Monocular Metric Depth Models for 3D Urban Asset Localization
by: Carnot, Miriam Louise, et al.
Published: (2025)

Depth Anything at Any Condition
by: Sun, Boyuan, et al.
Published: (2025)

DA$^{2}$: Depth Anything in Any Direction
by: Li, Haodong, et al.
Published: (2025)

FutureDepth: Learning to Predict the Future Improves Video Depth Estimation
by: Yasarla, Rajeev, et al.
Published: (2024)

Transferring Relative Monocular Depth to Surgical Vision with Temporal Consistency
by: Budd, Charlie, et al.
Published: (2024)

Adapting Depth Anything to Adverse Imaging Conditions with Events
by: Peng, Shihan, et al.
Published: (2026)

Depth Anything in Medical Images: A Comparative Study
by: Han, John J., et al.
Published: (2024)

Advancing Depth Anything Model for Unsupervised Monocular Depth Estimation in Endoscopy
by: Li, Bojian, et al.
Published: (2024)

Simplify Implant Depth Prediction as Video Grounding: A Texture Perceive Implant Depth Prediction Network
by: Yang, Xinquan, et al.
Published: (2024)

Unlocking the Potential of Operations Research for Multi-Graph Matching
by: Kahl, Max, et al.
Published: (2024)

Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
by: Yang, Lihe, et al.
Published: (2024)

Depth Anything in $360^\circ$: Towards Scale Invariance in the Wild
by: Jiang, Hualie, et al.
Published: (2025)

MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation
by: Yasarla, Rajeev, et al.
Published: (2023)

SpatioTemporal Difference Network for Video Depth Super-Resolution
by: Wang, Zhengxue, et al.
Published: (2025)

StableDPT: Temporal Stable Monocular Video Depth Estimation
by: Sobko, Ivan, et al.
Published: (2026)

DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos
by: Hu, Wenbo, et al.
Published: (2024)

Hierarchical Event Memory for Accurate and Low-latency Online Video Temporal Grounding
by: Zheng, Minghang, et al.
Published: (2025)

Flow and Depth Assisted Video Prediction with Latent Transformer
by: Suleyman, Eliyas, et al.
Published: (2025)

Video Depth Propagation
by: Piccinelli, Luigi, et al.
Published: (2025)