214 citations · 402 across the 27 of their papers we have counts for
27 papers
Depth Any Video with Scalable Synthetic Data
Honghui Yang, Di Huang, Wei Yin +6
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 introd…
SDGE: Stereo Guided Depth Estimation for 360 Camera Sets
Jialei Xu, Wei Yin, Dong Gong +2
Depth estimation is a critical technology in autonomous driving, and multi-camera systems are often used to achieve a 360 perception. These 360 camera sets often ha…
Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation
Mu Hu, Wei Yin, Chi Zhang +7
We introduce Metric3D v2, a geometric foundation model for zero-shot metric depth and surface normal estimation from a single image, which is crucial for metric 3D recovery. While…
Robust Geometry-Preserving Depth Estimation Using Differentiable Rendering
Chi Zhang, Wei Yin, Gang Yu +5
In this study, we address the challenge of 3D scene structure recovery from monocular depth estimation. While traditional depth estimation methods leverage labeled datasets to dire…
FrozenRecon: Pose-free 3D Scene Reconstruction with Frozen Depth Models
Guangkai Xu, Wei Yin, Hao Chen +3
3D scene reconstruction is a long-standing vision task. Existing approaches can be categorized into geometry-based and learning-based methods. The former leverages multi-view geome…
Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image
Wei Yin, Chi Zhang, Hao Chen +5
Reconstructing accurate 3D scenes from images is a long-standing vision task. Due to the ill-posedness of the single-image reconstruction problem, most well-established methods are…
The Second Monocular Depth Estimation Challenge
Jaime Spencer, C. Stella Qian, Michaela Trescakova +40
This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC). This edition was open to methods using any form of supervision, includin…
Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes
Rui Li, Dong Gong, Wei Yin +6
Multi-frame depth estimation generally achieves high accuracy relying on the multi-view geometric consistency. When applied in dynamic scenes, e.g., autonomous driving, this consis…
SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes
Libo Sun, Jia-Wang Bian, Huangying Zhan +3
Self-supervised monocular depth estimation has shown impressive results in static scenes. It relies on the multi-view consistency assumption for training networks, however, that is…
Hierarchical Normalization for Robust Monocular Depth Estimation
Chi Zhang, Wei Yin, Zhibin Wang +3
In this paper, we address monocular depth estimation with deep neural networks. To enable training of deep monocular estimation models with various sources of datasets, state-of-th…
Towards Accurate Reconstruction of 3D Scene Shape from A Single Monocular Image
Wei Yin, Jianming Zhang, Oliver Wang +4
Despite significant progress made in the past few years, challenges remain for depth estimation using a single monocular image. First, it is nontrivial to train a metric-depth pred…
Controllable Shadow Generation Using Pixel Height Maps
Yichen Sheng, Yifan Liu, Jianming Zhang +6
Shadows are essential for realistic image compositing. Physics-based shadow rendering methods require 3D geometries, which are not always available. Deep learning-based shadow synt…
Towards Domain-agnostic Depth Completion
Guangkai Xu, Wei Yin, Jianming Zhang +4
Existing depth completion methods are often targeted at a specific sparse depth type and generalize poorly across task domains. We present a method to complete sparse/semi-dense, n…
Exploiting Correspondences with All-pairs Correlations for Multi-view Depth Estimation
Kai Cheng, Hao Chen, Wei Yin +2
Multi-view depth estimation plays a critical role in reconstructing and understanding the 3D world. Recent learning-based methods have made significant progress in it. However, mul…
Improving Monocular Visual Odometry Using Learned Depth
Libo Sun, Wei Yin, Enze Xie +3
Monocular visual odometry (VO) is an important task in robotics and computer vision. Thus far, how to build accurate and robust monocular VO systems that can work well in diverse s…
PointInst3D: Segmenting 3D Instances by Points
Tong He, Wei Yin, Chunhua Shen +1
The current state-of-the-art methods in 3D instance segmentation typically involve a clustering step, despite the tendency towards heuristics, greedy algorithms, and a lack of robu…
Retrieval Augmented Classification for Long-Tail Visual Recognition
Alexander Long, Wei Yin, Thalaiyasingam Ajanthan +6
We introduce Retrieval Augmented Classification (RAC), a generic approach to augmenting standard image classification pipelines with an explicit retrieval module. RAC consists of a…
Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings
Wei Yin, Yifan Liu, Chunhua Shen +2
We propose an approach to semantic segmentation that achieves state-of-the-art supervised performance when applied in a zero-shot setting. It thus achieves results equivalent to th…
Towards 3D Scene Reconstruction from Locally Scale-Aligned Monocular Video Depth
Guangkai Xu, Wei Yin, Hao Chen +4
Existing monocular depth estimation methods have achieved excellent robustness in diverse scenes, but they can only retrieve affine-invariant depth, up to an unknown scale and shif…
Pseudo-LiDAR Based Road Detection
Libo Sun, Haokui Zhang, Wei Yin
Road detection is a critically important task for self-driving cars. By employing LiDAR data, recent works have significantly improved the accuracy of road detection. Relying on Li…
Generic Perceptual Loss for Modeling Structured Output Dependencies
Yifan Liu, Hao Chen, Yu Chen +2
The perceptual loss has been widely used as an effective loss term in image synthesis tasks including image super-resolution, and style transfer. It was believed that the success l…
Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Prediction
Wei Yin, Yifan Liu, Chunhua Shen
Monocular depth prediction plays a crucial role in understanding 3D scene geometry. Although recent methods have achieved impressive progress in terms of evaluation metrics such as…
Learning to Recover 3D Scene Shape from a Single Image
Wei Yin, Jianming Zhang, Oliver Wang +4
Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art methods cannot be used to recover accurate 3D scene shape due to an unknown depth sh…
DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data
Wei Yin, Xinlong Wang, Chunhua Shen +5
We present a method for depth estimation with monocular images, which can predict high-quality depth on diverse scenes up to an affine transformation, thus preserving accurate shap…