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Foundation Models Defining a New Era in Vision: a Survey and Outlook
Vision systems that see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …
fundamental to understanding our world. The complex relations between objects and their …
Vision-language pre-training: Basics, recent advances, and future trends
This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …
intelligence that have been developed in the last few years. We group these approaches …
Cogvlm: Visual expert for pretrained language models
We introduce CogVLM, a powerful open-source visual language foundation model. Different
from the popular\emph {shallow alignment} method which maps image features into the …
from the popular\emph {shallow alignment} method which maps image features into the …
Sharegpt4v: Improving large multi-modal models with better captions
Modality alignment serves as the cornerstone for large multi-modal models (LMMs).
However, the impact of different attributes (eg, data type, quality, and scale) of training data …
However, the impact of different attributes (eg, data type, quality, and scale) of training data …
Multimodal foundation models: From specialists to general-purpose assistants
Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …
methods to data compression. Recent advances in statistical machine learning have opened …
Yolo-world: Real-time open-vocabulary object detection
Abstract The You Only Look Once (YOLO) series of detectors have established themselves
as efficient and practical tools. However their reliance on predefined and trained object …
as efficient and practical tools. However their reliance on predefined and trained object …
Grounded sam: Assembling open-world models for diverse visual tasks
We introduce Grounded SAM, which uses Grounding DINO as an open-set object detector to
combine with the segment anything model (SAM). This integration enables the detection and …
combine with the segment anything model (SAM). This integration enables the detection and …
Vid2seq: Large-scale pretraining of a visual language model for dense video captioning
In this work, we introduce Vid2Seq, a multi-modal single-stage dense event captioning
model pretrained on narrated videos which are readily-available at scale. The Vid2Seq …
model pretrained on narrated videos which are readily-available at scale. The Vid2Seq …
Eva: Exploring the limits of masked visual representation learning at scale
We launch EVA, a vision-centric foundation model to explore the limits of visual
representation at scale using only publicly accessible data. EVA is a vanilla ViT pre-trained …
representation at scale using only publicly accessible data. EVA is a vanilla ViT pre-trained …
Internimage: Exploring large-scale vision foundation models with deformable convolutions
Compared to the great progress of large-scale vision transformers (ViTs) in recent years,
large-scale models based on convolutional neural networks (CNNs) are still in an early …
large-scale models based on convolutional neural networks (CNNs) are still in an early …