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Found 2 papers, 1 papers with code
Weakly Supervised Gaussian Contrastive Grounding with Large Multimodal Models for Video Question Answering
GCG learns multiple Gaussian functions to characterize the temporal structure of the video, and sample question-critical frames as positive moments to be the visual inputs of LMMs.
Weakly Supervised Learning of Semantic Correspondence through Cascaded Online Correspondence Refinement
Following the spirit of multiple instance learning (MIL), we decompose the weakly supervised correspondence learning problem into three stages: image-level matching, region-level matching, and pixel-level matching.
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