View-consistent sampling driven by color and distilled DINOv2 features, plus a depth-pushing loss, improves NeRF novel-view synthesis over depth-based regularizers.
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A View-consistent Sampling Method for Regularized Training of Neural Radiance Fields
View-consistent sampling driven by color and distilled DINOv2 features, plus a depth-pushing loss, improves NeRF novel-view synthesis over depth-based regularizers.