Omni-DeepSearch is a 640-sample benchmark for audio-driven omni-modal search where the best model reaches only 43.44% accuracy, exposing bottlenecks in audio inference, tool use, and cross-modal reasoning.
arXiv preprint arXiv:2312.03816 , year=
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HL-OutPaint enables high-resolution outpainting of long video sequences via a coarse-to-fine pipeline that first builds Global Coarse Guidance through global-local frame swapping then synthesizes details.
M-GDM uses motion vectors and frame types to guide a diffusion model in blind recovery of bitstream-corrupted videos without manual masks.
citing papers explorer
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Omni-DeepSearch: A Benchmark for Audio-Driven Omni-Modal Deep Search
Omni-DeepSearch is a 640-sample benchmark for audio-driven omni-modal search where the best model reaches only 43.44% accuracy, exposing bottlenecks in audio inference, tool use, and cross-modal reasoning.
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HL-OutPaint: Coarse-to-Fine Video Outpainting for High-Resolution Long-Range Videos
HL-OutPaint enables high-resolution outpainting of long video sequences via a coarse-to-fine pipeline that first builds Global Coarse Guidance through global-local frame swapping then synthesizes details.
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Blind Bitstream-corrupted Video Recovery via Metadata-guided Diffusion Model
M-GDM uses motion vectors and frame types to guide a diffusion model in blind recovery of bitstream-corrupted videos without manual masks.