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[HTML][HTML] Review of large vision models and visual prompt engineering
Visual prompt engineering is a fundamental methodology in the field of visual and image
artificial general intelligence. As the development of large vision models progresses, the …
artificial general intelligence. As the development of large vision models progresses, the …
Long-clip: Unlocking the long-text capability of clip
Abstract Contrastive Language-Image Pre-training (CLIP) has been the cornerstone for zero-
shot classification, text-image retrieval, and text-image generation by aligning image and …
shot classification, text-image retrieval, and text-image generation by aligning image and …
Egovlpv2: Egocentric video-language pre-training with fusion in the backbone
Video-language pre-training (VLP) has become increasingly important due to its ability to
generalize to various vision and language tasks. However, existing egocentric VLP …
generalize to various vision and language tasks. However, existing egocentric VLP …
Fusecap: Leveraging large language models for enriched fused image captions
The advent of vision-language pre-training techniques enhanced substantial progress in the
development of models for image captioning. However, these models frequently produce …
development of models for image captioning. However, these models frequently produce …
Sa-attack: Improving adversarial transferability of vision-language pre-training models via self-augmentation
Apollo: unified adapter and prompt learning for vision language models
The choice of input text prompt plays a critical role in the performance of Vision-Language
Pretrained (VLP) models such as CLIP. We present APoLLo, a unified multi-modal approach …
Pretrained (VLP) models such as CLIP. We present APoLLo, a unified multi-modal approach …
Groundvlp: Harnessing zero-shot visual grounding from vision-language pre-training and open-vocabulary object detection
Visual grounding, a crucial vision-language task involving the understanding of the visual
context based on the query expression, necessitates the model to capture the interactions …
context based on the query expression, necessitates the model to capture the interactions …
Gradient-based visual explanation for transformer-based clip
Significant progress has been achieved on the improvement and downstream usages of the
Contrastive Language-Image Pre-training (CLIP) vision-language model, while less …
Contrastive Language-Image Pre-training (CLIP) vision-language model, while less …
Learning to learn better visual prompts
Prompt tuning provides a low-cost way of adapting vision-language models (VLMs) for
various downstream vision tasks without requiring updating the huge pre-trained …
various downstream vision tasks without requiring updating the huge pre-trained …