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Found 5 papers, 5 papers with code
Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera
DAC achieves state-of-the-art zero-shot metric depth estimation, improving $\delta_1$ accuracy by up to 50% on multiple fisheye and 360-degree datasets compared to prior metric depth foundation models, demonstrating robust generalization across camera types.
Scale-Invariant Monocular Depth Estimation via SSI Depth
Existing methods for scale-invariant monocular depth estimation (SI MDE) often struggle due to the complexity of the task, and limited and non-diverse datasets, hindering generalizability in real-world scenarios.
Intrinsic Harmonization for Illumination-Aware Compositing
Despite significant advancements in network-based image harmonization techniques, there still exists a domain disparity between typical training pairs and real-world composites encountered during inference.
Realistic Saliency Guided Image Enhancement
We thus offer a viable solution for automating image enhancement and photo cleanup operations.
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging
Neural networks have shown great abilities in estimating depth from a single image.
Ranked #1 on
Monocular Depth Estimation
on IBims-1
