EventPrune prunes 80% of visual tokens in Video-LLMs using event camera motion cues, yielding 1.89x speedup, 52% fewer GFLOPs, and slightly higher accuracy than full-token baselines on first-person dynamic spatial reasoning.
Eventclip: Adapting clip for event- based object recognition
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cs.CV 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
EventFace achieves 94.19% Rank-1 accuracy and 5.35% EER on a new small event-based face dataset by transferring facial structure priors via LoRA and fusing them with temporal motion features.
GEP transfers semantic knowledge from image foundation models to event data via alignment and generative pretraining on mixed sequences to create transferable event-based visual models.
RE-VLM fuses RGB and event data in a dual-stream VLM with a graph-based pipeline for generating training captions and QA pairs, plus two new datasets, showing gains over RGB-only and event-only baselines especially in challenging conditions.
citing papers explorer
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EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning
EventPrune prunes 80% of visual tokens in Video-LLMs using event camera motion cues, yielding 1.89x speedup, 52% fewer GFLOPs, and slightly higher accuracy than full-token baselines on first-person dynamic spatial reasoning.
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EventFace: Event-Based Face Recognition via Structure-Driven Spatiotemporal Modeling
EventFace achieves 94.19% Rank-1 accuracy and 5.35% EER on a new small event-based face dataset by transferring facial structure priors via LoRA and fusing them with temporal motion features.
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Generative Event Pretraining with Foundation Model Alignment
GEP transfers semantic knowledge from image foundation models to event data via alignment and generative pretraining on mixed sequences to create transferable event-based visual models.
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RE-VLM: Event-Augmented Vision-Language Model for Scene Understanding
RE-VLM fuses RGB and event data in a dual-stream VLM with a graph-based pipeline for generating training captions and QA pairs, plus two new datasets, showing gains over RGB-only and event-only baselines especially in challenging conditions.