MODEST provides the first large-scale high-resolution stereo DSLR dataset with systematic variation of focal length and aperture to support research on real-world optical effects in depth estimation.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
FreeOcc enables training-free open-vocabulary 3D occupancy prediction from RGB-D sequences by combining SLAM, dense Gaussian maps, off-the-shelf vision-language models, and probabilistic projection, achieving over 2x gains on benchmarks and zero-shot transfer to novel scenes.
DINO features combined with many-to-many association and the proposed Harmonic Consensus Maximization enable general visual features to compete with specialized models on out-of-distribution image matching and camera pose estimation.
citing papers explorer
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MODEST: Multi-Optics Depth-of-Field Stereo Dataset
MODEST provides the first large-scale high-resolution stereo DSLR dataset with systematic variation of focal length and aperture to support research on real-world optical effects in depth estimation.
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FreeOcc: Training-Free Embodied Open-Vocabulary Occupancy Prediction
FreeOcc enables training-free open-vocabulary 3D occupancy prediction from RGB-D sequences by combining SLAM, dense Gaussian maps, off-the-shelf vision-language models, and probabilistic projection, achieving over 2x gains on benchmarks and zero-shot transfer to novel scenes.
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Deploy DINO with Many-to-Many Association
DINO features combined with many-to-many association and the proposed Harmonic Consensus Maximization enable general visual features to compete with specialized models on out-of-distribution image matching and camera pose estimation.