CloudLULC-Net is an end-to-end heterogeneous SAR-optical fusion network for LULC mapping under cloud contamination that achieves 86.60% OA, 83.29% F1, and 73.51% mIoU on a new global benchmark of 40,223 samples.
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V-Net: Fully Convolutional Neural Networks for V olumetric Medical Image Segmentation
15 Pith papers cite this work. Polarity classification is still indexing.
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HumanFlow is a latent diffusion model for unified human motion tracking and forecasting in 3D scenes, tightly coupled via flow-matching MPC to an approximate policy for MAV social navigation that outperforms prior methods in simulation under partial observability.
ESARBench is the first unified benchmark for MLLM-driven UAV agents that must explore, locate clues, and decide on victim positions in photorealistic simulated SAR environments.
FastForward represents scenes as collections of 3D-anchored image features and performs camera pose estimation via feed-forward correspondence prediction, achieving competitive accuracy with minimal mapping time.
Introduces LSM that outputs calibrated multimodal spatial distributions from language plus scene graph, fused via VL-Map to improve 3D target localization on VLA-3D benchmark and real robot.
MuNet is an end-to-end graph convolutional network using 2-manifold graphs and a mutualistic training mechanism that jointly optimizes 3D human mesh recovery and clothed reconstruction, reporting state-of-the-art results on six benchmarks.
Frozen DINOv3 features with multi-view MLP probes, entropy-weighted fusion, and spatial regularization achieve 0.895 Dice on Kvasir-SEG, 0.897 on ISIC 2018, and 0.908 on BraTS FLAIR, recovering 98.4% of full-data performance with only five annotated patients.
Moondream Segmentation achieves 80.2% cIoU on RefCOCO by autoregressively decoding paths from referring expressions and using RL to refine masks, plus releases a cleaned RefCOCO-M dataset.
DSER combines spectral epipolar regularization with a hybrid pipeline of gradient initialization, plane-sweeping, multiscale refinement, and occlusion-aware random walk to produce structurally consistent depth maps from light fields.
Qwen-RobotNav provides a parameterized navigation model trained on 15.6M samples with vision-language co-training that achieves SOTA results on benchmarks and zero-shot transfer to real robots.
Ada2MS is a new optimizer that exponentially mixes elementwise and global second-moment estimates to interpolate between AdamW and momentum-SGD behaviors and reports competitive results on visual tasks under a unified protocol.
Presents Instant3D for rapid text/image-to-3D generation via multi-view diffusion plus feed-forward reconstruction, and FastMap for 10x faster structure-from-motion with comparable accuracy.
MixTGFormer reports state-of-the-art 3D pose estimation errors of 37.6 mm on Human3.6M and 15.7 mm on MPI-INF-3DHP by using parallel GCN-Transformer streams with SE layers for local-global feature fusion.
A multilevel perceptual CRF model using Swin Transformer, HPF fusion, HA adapters, and dynamic scaling attention achieves state-of-the-art monocular depth estimation on NYU Depth v2, KITTI, and MatterPort3D with reduced error and fast inference.
TMVA4D uses CNN and ConvLSTM encoders on multi-view 2D projections of 4D radar point clouds for semantic segmentation of people, reporting Dice 75.9% and IoU 61.2% in field tests.
citing papers explorer
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Heterogeneous SAR-optical fusion for near-real-time land use and land cover mapping under cloud contamination: A novel framework and global benchmark dataset
CloudLULC-Net is an end-to-end heterogeneous SAR-optical fusion network for LULC mapping under cloud contamination that achieves 86.60% OA, 83.29% F1, and 73.51% mIoU on a new global benchmark of 40,223 samples.
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HumanFlow -- Diffusion-Driven MAV Navigation Among Humans via Tightly-Coupled Motion Tracking, Forecasting, and Control
HumanFlow is a latent diffusion model for unified human motion tracking and forecasting in 3D scenes, tightly coupled via flow-matching MPC to an approximate policy for MAV social navigation that outperforms prior methods in simulation under partial observability.
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ESARBench: A Benchmark for Agentic UAV Embodied Search and Rescue
ESARBench is the first unified benchmark for MLLM-driven UAV agents that must explore, locate clues, and decide on victim positions in photorealistic simulated SAR environments.
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A Scene is Worth a Thousand Features: Feed-Forward Camera Localization from a Collection of Image Features
FastForward represents scenes as collections of 3D-anchored image features and performs camera pose estimation via feed-forward correspondence prediction, achieving competitive accuracy with minimal mapping time.
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Language as a Sensor: Calibrated Spatial Belief Estimation in 3D Scenes from Natural Language
Introduces LSM that outputs calibrated multimodal spatial distributions from language plus scene graph, fused via VL-Map to improve 3D target localization on VLA-3D benchmark and real robot.
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MuNet: A Mutualistic Network for Joint 3D Human Mesh Recovery and 3D Clothed Human Reconstruction from Single Images
MuNet is an end-to-end graph convolutional network using 2-manifold graphs and a mutualistic training mechanism that jointly optimizes 3D human mesh recovery and clothed reconstruction, reporting state-of-the-art results on six benchmarks.
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DINO-MVR: Multi-View Readout of Frozen DINOv3 for Annotation-Efficient Medical Segmentation
Frozen DINOv3 features with multi-view MLP probes, entropy-weighted fusion, and spatial regularization achieve 0.895 Dice on Kvasir-SEG, 0.897 on ISIC 2018, and 0.908 on BraTS FLAIR, recovering 98.4% of full-data performance with only five annotated patients.
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Moondream Segmentation: From Words to Masks
Moondream Segmentation achieves 80.2% cIoU on RefCOCO by autoregressively decoding paths from referring expressions and using RL to refine masks, plus releases a cleaned RefCOCO-M dataset.
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DSER: Spectral Epipolar Representation for Efficient Light Field Depth Estimation
DSER combines spectral epipolar regularization with a hybrid pipeline of gradient initialization, plane-sweeping, multiscale refinement, and occlusion-aware random walk to produce structurally consistent depth maps from light fields.
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Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation System
Qwen-RobotNav provides a parameterized navigation model trained on 15.6M samples with vision-language co-training that achieves SOTA results on benchmarks and zero-shot transfer to real robots.
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Ada2MS: A Hybrid Optimization Algorithm Based on Exponential Mixing of Elementwise and Global Second-Moment Estimates
Ada2MS is a new optimizer that exponentially mixes elementwise and global second-moment estimates to interpolate between AdamW and momentum-SGD behaviors and reports competitive results on visual tasks under a unified protocol.
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Efficient 3D Content Reconstruction and Generation
Presents Instant3D for rapid text/image-to-3D generation via multi-view diffusion plus feed-forward reconstruction, and FastMap for 10x faster structure-from-motion with comparable accuracy.
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Dual-stream Spatio-Temporal GCN-Transformer Network for 3D Human Pose Estimation
MixTGFormer reports state-of-the-art 3D pose estimation errors of 37.6 mm on Human3.6M and 15.7 mm on MPI-INF-3DHP by using parallel GCN-Transformer streams with SE layers for local-global feature fusion.
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Hierarchical Awareness Adapters with Hybrid Pyramid Feature Fusion for Dense Depth Prediction
A multilevel perceptual CRF model using Swin Transformer, HPF fusion, HA adapters, and dynamic scaling attention achieves state-of-the-art monocular depth estimation on NYU Depth v2, KITTI, and MatterPort3D with reduced error and fast inference.
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4D Radar Semantic Segmentation of People in Field Conditions Using Temporal Multi-View Networks
TMVA4D uses CNN and ConvLSTM encoders on multi-view 2D projections of 4D radar point clouds for semantic segmentation of people, reporting Dice 75.9% and IoU 61.2% in field tests.