WildRelight: Real-World Benchmark for Single-Image Relighting
Researchers have introduced WildRelight, the first in-the-wild dataset for evaluating single-image relighting models. Current synthetic benchmarks fail to capture real-world complexity, causing domain shifts in state-of-the-art models. WildRelight features high-resolution outdoor scenes with aligned, temporally varying natural illuminations and high-dynamic-range environment maps. The dataset aims to bridge the synthetic-to-real gap in relighting research.
Key facts
- WildRelight is the first in-the-wild dataset for single-image relighting evaluation.
- Dataset includes high-resolution outdoor scenes with aligned natural illuminations.
- Each scene is paired with a high-dynamic-range environment map.
- State-of-the-art models trained on synthetic data show severe domain shifts.
- Current datasets are designed for multi-view reconstruction, not relighting.
- WildRelight addresses the synthetic-to-real gap in relighting.
- The dataset features temporally varying natural illuminations.
- A rigorous benchmark was established using WildRelight.
Entities
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