ST-GD adapts Grounding DINO with about 10 million trainable parameters via adapters and a temporal decoder to achieve competitive performance on limited-data spatio-temporal video grounding benchmarks.
Continual learning for vlms: A survey and taxonomy beyond forgetting, 2025
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Unlocking the Potential of Grounding DINO in Videos: Parameter-Efficient Adaptation for Limited-Data Spatial-Temporal Localization
ST-GD adapts Grounding DINO with about 10 million trainable parameters via adapters and a temporal decoder to achieve competitive performance on limited-data spatio-temporal video grounding benchmarks.