Pinned Repositories
AudST
Awesome-Video-Diffusion
A curated list of recent diffusion models for video generation, editing, restoration, understanding, etc.
DFRQ
Deep Fourier Ranking Quantization for Semi-Supervised Image Retrieval -- TIP22
DKPH
Dual-Stream Knowledge-Preserving Hashing for Unsupervised Video Retrieval ECCV22
fucking-algorithm
刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.
lpd
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
MESM
The official code of Towards Balanced Alignment: Modal-Enhanced Semantic Modeling for Video Moment Retrieval
MomentDiff
MomentDiff: Generative Video Moment Retrieval from Random to Real--NeurIPS 2023
NASA
Neighborhood-Adaptive Structure Augmented Metric Learning -- AAAI2022 oral
ProST
Progressive Spatio-Temporal Prototype Matching for Text-Video Retrieval --ICCV2023 Oral
IMCCretrieval's Repositories
IMCCretrieval/ProST
Progressive Spatio-Temporal Prototype Matching for Text-Video Retrieval --ICCV2023 Oral
IMCCretrieval/MomentDiff
MomentDiff: Generative Video Moment Retrieval from Random to Real--NeurIPS 2023
IMCCretrieval/NASA
Neighborhood-Adaptive Structure Augmented Metric Learning -- AAAI2022 oral
IMCCretrieval/DKPH
Dual-Stream Knowledge-Preserving Hashing for Unsupervised Video Retrieval ECCV22
IMCCretrieval/DFRQ
Deep Fourier Ranking Quantization for Semi-Supervised Image Retrieval -- TIP22
IMCCretrieval/AudST
IMCCretrieval/Awesome-Video-Diffusion
A curated list of recent diffusion models for video generation, editing, restoration, understanding, etc.
IMCCretrieval/fucking-algorithm
刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.
IMCCretrieval/lpd
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
IMCCretrieval/MESM
The official code of Towards Balanced Alignment: Modal-Enhanced Semantic Modeling for Video Moment Retrieval
IMCCretrieval/unmasked_teacher
[ICCV2023 Oral] Unmasked Teacher: Towards Training-Efficient Video Foundation Models