RefAerial is a new benchmark dataset for text-based object detection in aerial imagery, accompanied by an SCS model that handles scale diversity better than prior ground-image methods.
Bert: Pre-training of deep bidirectional trans- formers for language understanding
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MoGaF groups Gaussians by motion in 4D splatting representations to enable stable long-term forecasting of dynamic scenes.
PET-DINO unifies visual and text prompts in Grounding DINO via an alignment-friendly generation module and prompt-enriched training strategies to improve zero-shot open-set object detection.
citing papers explorer
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RefAerial: A Benchmark and Approach for Referring Detection in Aerial Images
RefAerial is a new benchmark dataset for text-based object detection in aerial imagery, accompanied by an SCS model that handles scale diversity better than prior ground-image methods.
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Space-Time Forecasting of Dynamic Scenes with Motion-aware Gaussian Grouping
MoGaF groups Gaussians by motion in 4D splatting representations to enable stable long-term forecasting of dynamic scenes.
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PET-DINO: Unifying Visual Cues into Grounding DINO with Prompt-Enriched Training
PET-DINO unifies visual and text prompts in Grounding DINO via an alignment-friendly generation module and prompt-enriched training strategies to improve zero-shot open-set object detection.