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Internvid: A large-scale video-text dataset for multimodal understanding and generation
This paper introduces InternVid, a large-scale video-centric multimodal dataset that enables
learning powerful and transferable video-text representations for multimodal understanding …
learning powerful and transferable video-text representations for multimodal understanding …
Language-based action concept spaces improve video self-supervised learning
Recent contrastive language image pre-training has led to learning highly transferable and
robust image representations. However, adapting these models to video domain with …
robust image representations. However, adapting these models to video domain with …
Multi-granularity correspondence learning from long-term noisy videos
Existing video-language studies mainly focus on learning short video clips, leaving long-
term temporal dependencies rarely explored due to over-high computational cost of …
term temporal dependencies rarely explored due to over-high computational cost of …
Mug-STAN: adapting image-language pretrained models for general video understanding
Large-scale image-language pretrained models, eg, CLIP, have demonstrated remarkable
proficiency in acquiring general multi-modal knowledge through web-scale image-text data …
proficiency in acquiring general multi-modal knowledge through web-scale image-text data …
Tvtsv2: Learning out-of-the-box spatiotemporal visual representations at scale
The ultimate goal for foundation models is realizing task-agnostic, ie, supporting out-of-the-
box usage without task-specific fine-tuning. Although breakthroughs have been made in …
box usage without task-specific fine-tuning. Although breakthroughs have been made in …
Themis: A passive-active hybrid framework with in-network intelligence for lightweight failure localization
The fast and efficient failure detection and localization is essential for stable network
transmission. Unfortunately, existing schemes suffer from a few drawbacks such as …
transmission. Unfortunately, existing schemes suffer from a few drawbacks such as …
Video-Language Alignment via Spatio-Temporal Graph Transformer
Video-language alignment is a crucial multi-modal task that benefits various downstream
applications, eg, video-text retrieval and video question answering. Existing methods either …
applications, eg, video-text retrieval and video question answering. Existing methods either …
Concap: contrastive context-aware prompt for resource-hungry action recognition
Existing large-scale image-language pre-trained models, eg, CLIP [1], have revealed strong
spatial recognition capability on various vision tasks. However, they achieve inferior …
spatial recognition capability on various vision tasks. However, they achieve inferior …