Latest Research in Computer Vision and Pattern Recognition

40 research papers · 2026 median publication year

Top Research Topics in Computer Vision and Pattern Recognition

Highest-Cited Papers

  1. Autonomous docking experiments for underwater spherical robot based on visual guidance with improved detection transformer
  2. PolyLayout: Multi-room Manhattan Layout Estimation
  3. Efficient Monocular Depth Estimation on Embedded Systems with Neural Cellular Automata
  4. Gaussian Belief Propagation Network for Depth Completion
  5. RIDE: Relocalization-Informed Depth Estimation with 3D Gaussian Splatting
  6. Reducing Depth Measurement Uncertainty in Industrial Robot Stereo Vision Through Error-Aware Disparity Refinement
  7. Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
  8. GALoc: Gravity Aligned Wireframes for Depth-Free Monocular Floorplan Localization
  9. OmniPoint: Universal Monocular Metric Pointcloud from Any Camera
  10. Online dynamic scene reconstruction based on multi-view video
  11. UniFusion: Sparse-View 4D Reconstruction via Unified Spatio-temporal Depth Alignment
  12. Towards Robust Driving Perception: A Flexible Scale-Driven Family for Self-Supervised Monocular Depth Estimation
  13. AI-based single-shot structured-light depth reconstruction for real-time laparoscopic surgical guidance
  14. CrossDepth: Geometry-Constrained Attention for Generalizable Multi-View Surround Depth Estimation
  15. Weather-Conditioned Depth Anything
  16. Pixel-wise Planarity for High-Precision Monocular Plane Segmentation
  17. Vision3D: A Full-Stack Framework for Monocular Single-Image 3D Scene Reconstruction with Depth– Object Semantic Fusion
  18. Vision3D: A Full-Stack Framework for Monocular Single-Image 3D Scene Reconstruction with Depth– Object Semantic Fusion
  19. When Depth Hurts: Reliability-Aware Geometry Distillation for Depth-Free RGB-D Salient Object Detection
  20. Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations
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L3 Region - - 2026 Sep Q3

Computer Vision and Pattern Recognition

40 papers

Top Topics (8)

Computer Vision and Pattern Recognition26
Advanced Vision and Imaging6
Image and Video Processing2
Robotics and Sensor-Based Localization2
Underwater Vehicles and Communication Systems1
Robotics1
Optics1
Zebrafish Biomedical Research Applications1

Top Publications (20)

1.Autonomous docking experiments for underwater spherical robot based on visual guidance with improved detection transformer2.PolyLayout: Multi-room Manhattan Layout Estimation3.Efficient Monocular Depth Estimation on Embedded Systems with Neural Cellular Automata4.Gaussian Belief Propagation Network for Depth Completion5.RIDE: Relocalization-Informed Depth Estimation with 3D Gaussian Splatting6.Reducing Depth Measurement Uncertainty in Industrial Robot Stereo Vision Through Error-Aware Disparity Refinement7.Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation8.GALoc: Gravity Aligned Wireframes for Depth-Free Monocular Floorplan Localization9.OmniPoint: Universal Monocular Metric Pointcloud from Any Camera10.Online dynamic scene reconstruction based on multi-view video11.UniFusion: Sparse-View 4D Reconstruction via Unified Spatio-temporal Depth Alignment12.Towards Robust Driving Perception: A Flexible Scale-Driven Family for Self-Supervised Monocular Depth Estimation13.AI-based single-shot structured-light depth reconstruction for real-time laparoscopic surgical guidance14.CrossDepth: Geometry-Constrained Attention for Generalizable Multi-View Surround Depth Estimation15.Weather-Conditioned Depth Anything16.Pixel-wise Planarity for High-Precision Monocular Plane Segmentation17.Vision3D: A Full-Stack Framework for Monocular Single-Image 3D Scene Reconstruction with Depth– Object Semantic Fusion18.Vision3D: A Full-Stack Framework for Monocular Single-Image 3D Scene Reconstruction with Depth– Object Semantic Fusion19.When Depth Hurts: Reliability-Aware Geometry Distillation for Depth-Free RGB-D Salient Object Detection20.Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations
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