SOTAVerified

Depth Prediction

Papers

Showing 150 of 422 papers

TitleStatusHype
pySLAM: An Open-Source, Modular, and Extensible Framework for SLAMCode7
FeatUp: A Model-Agnostic Framework for Features at Any ResolutionCode5
Uni4D: Unifying Visual Foundation Models for 4D Modeling from a Single VideoCode3
DROID-Splat: Combining end-to-end SLAM with 3D Gaussian SplattingCode3
DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular VideosCode3
ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth EstimationCode3
Denoising Vision TransformersCode3
SimpleRecon: 3D Reconstruction Without 3D ConvolutionsCode3
Towards Accurate Reconstruction of 3D Scene Shape from A Single Monocular ImageCode3
MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error PriorsCode2
Few-shot Novel View Synthesis using Depth Aware 3D Gaussian SplattingCode2
Plane2Depth: Hierarchical Adaptive Plane Guidance for Monocular Depth EstimationCode2
Diffusion Models for Monocular Depth Estimation: Overcoming Challenging ConditionsCode2
MonoCD: Monocular 3D Object Detection with Complementary DepthsCode2
RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric ScaleCode2
CompletionFormer: Depth Completion with Convolutions and Vision TransformersCode2
Self-Supervised Learning from Images with a Joint-Embedding Predictive ArchitectureCode2
Behind the Scenes: Density Fields for Single View ReconstructionCode2
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View CompletionCode2
Map-free Visual Relocalization: Metric Pose Relative to a Single ImageCode2
Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and DenoisingCode2
NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth EstimationCode2
Rethinking Depth Estimation for Multi-View Stereo: A Unified RepresentationCode2
Extracting Triangular 3D Models, Materials, and Lighting From ImagesCode2
Sparse Auxiliary Networks for Unified Monocular Depth Prediction and CompletionCode2
Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth PredictionCode2
Learning to Recover 3D Scene Shape from a Single ImageCode2
Semantically-Guided Representation Learning for Self-Supervised Monocular DepthCode2
Enforcing geometric constraints of virtual normal for depth predictionCode2
MonoMVSNet: Monocular Priors Guided Multi-View Stereo NetworkCode1
Edge-Enabled VIO with Long-Tracked Features for High-Accuracy Low-Altitude IoT NavigationCode1
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
MVSDet: Multi-View Indoor 3D Object Detection via Efficient Plane SweepsCode1
EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth PredictionCode1
GroCo: Ground Constraint for Metric Self-Supervised Monocular DepthCode1
ProDepth: Boosting Self-Supervised Multi-Frame Monocular Depth with Probabilistic FusionCode1
Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D PerceptionCode1
Depth-aware Test-Time Training for Zero-shot Video Object SegmentationCode1
NeRF-Det++: Incorporating Semantic Cues and Perspective-aware Depth Supervision for Indoor Multi-View 3D DetectionCode1
RIDERS: Radar-Infrared Depth Estimation for Robust SensingCode1
A Concise but High-performing Network for Image Guided Depth Completion in Autonomous DrivingCode1
Global and Hierarchical Geometry Consistency Priors for Few-shot NeRFs in Indoor ScenesCode1
Learning Deformable Hypothesis Sampling for Accurate PatchMatch Multi-View StereoCode1
Camera-based 3D Semantic Scene Completion with Sparse Guidance NetworkCode1
Sparse Beats Dense: Rethinking Supervision in Radar-Camera Depth CompletionCode1
MonoProb: Self-Supervised Monocular Depth Estimation with Interpretable UncertaintyCode1
Metrically Scaled Monocular Depth Estimation through Sparse Priors for Underwater RobotsCode1
Stanford-ORB: A Real-World 3D Object Inverse Rendering BenchmarkCode1
ConsistNet: Enforcing 3D Consistency for Multi-view Images DiffusionCode1
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenesCode1
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