OmniVTG creates a new large-scale open-world VTG dataset using iterative concept-gap filling and timestamped captioning, paired with a three-stage self-correction CoT paradigm that yields SOTA zero-shot results on four existing benchmarks.
3d vision and language pre- training with large-scale synthetic data
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Chorus pretrains a shared 3D Gaussian scene encoder via multi-teacher distillation to capture holistic features from high-level semantics to fine-grained structure, with strong transfer on segmentation and point-cloud tasks using far fewer scenes.
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OmniVTG: A Large-Scale Dataset and Training Paradigm for Open-World Video Temporal Grounding
OmniVTG creates a new large-scale open-world VTG dataset using iterative concept-gap filling and timestamped captioning, paired with a three-stage self-correction CoT paradigm that yields SOTA zero-shot results on four existing benchmarks.
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Chorus: Multi-Teacher Pretraining for Holistic 3D Gaussian Scene Encoding
Chorus pretrains a shared 3D Gaussian scene encoder via multi-teacher distillation to capture holistic features from high-level semantics to fine-grained structure, with strong transfer on segmentation and point-cloud tasks using far fewer scenes.