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09/18/2023
Multimodal Foundation Models: From Specialists to General-Purpose Assistants
This paper presents a comprehensive survey of the taxonomy and evolution...
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09/18/2023
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Visual instruction tuning has recently shown encouraging progress with o...
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06/01/2023
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day
Conversational generative AI has demonstrated remarkable promise for emp...
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01/17/2023
Learning Customized Visual Models with Retrieval-Augmented Knowledge
Image-text contrastive learning models such as CLIP have demonstrated st...
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01/17/2023
GLIGEN: Open-Set Grounded Text-to-Image Generation
Large-scale text-to-image diffusion models have made amazing advances. H...
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12/21/2022
Generalized Decoding for Pixel, Image, and Language
We present X-Decoder, a generalized decoding model that can predict pixe...
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04/22/2022
Multimodal Adaptive Distillation for Leveraging Unimodal Encoders for Vision-Language Tasks
Cross-modal encoders for vision-language (VL) tasks are often pretrained...
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04/20/2022
K-LITE: Learning Transferable Visual Models with External Knowledge
Recent state-of-the-art computer vision systems are trained from natural...
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04/19/2022
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models
Learning visual representations from natural language supervision has re...
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04/07/2022
Unified Contrastive Learning in Image-Text-Label Space
Visual recognition is recently learned via either supervised learning on...
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03/29/2022
Parameter-efficient Fine-tuning for Vision Transformers
In computer vision, it has achieved great success in adapting large-scal...
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03/22/2022
Focal Modulation Networks
In this work, we propose focal modulation network (FocalNet in short), w...
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01/15/2022
CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks
Contrastive language-image pretraining (CLIP) links vision and language ...
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12/16/2021
RegionCLIP: Region-based Language-Image Pretraining
Contrastive language-image pretraining (CLIP) using image-text pairs has...
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12/07/2021
Grounded Language-Image Pre-training
This paper presents a grounded language-image pre-training (GLIP) model ...
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11/22/2021
Florence: A New Foundation Model for Computer Vision
Automated visual understanding of our diverse and open world demands com...
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09/06/2021
Learning to Generate Scene Graph from Natural Language Supervision
Learning from image-text data has demonstrated recent success for many r...
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08/23/2021
TACo: Token-aware Cascade Contrastive Learning for Video-Text Alignment
Contrastive learning has been widely used to train transformer-based vis...
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07/27/2021
Image Scene Graph Generation (SGG) Benchmark
There is a surge of interest in image scene graph generation (object, at...
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07/01/2021
Focal Self-attention for Local-Global Interactions in Vision Transformers
Recently, Vision Transformer and its variants have shown great promise o...
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06/17/2021
Efficient Self-supervised Vision Transformers for Representation Learning
This paper investigates two techniques for developing efficient self-sup...
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03/29/2021
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding
This paper presents a new Vision Transformer (ViT) architecture Multi-Sc...
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01/02/2021
VinVL: Making Visual Representations Matter in Vision-Language Models
This paper presents a detailed study of improving visual representations...
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12/21/2020
Object-Centric Diagnosis of Visual Reasoning
When answering questions about an image, it not only needs knowing what ...
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11/18/2020
Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language
Neuro-symbolic representations have proved effective in learning structu...
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04/09/2019
Embodied Visual Recognition
Passive visual systems typically fail to recognize objects in the amodal...
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10/01/2018
Visual Curiosity: Learning to Ask Questions to Learn Visual Recognition
In an open-world setting, it is inevitable that an intelligent agent (e....
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08/01/2018
Graph R-CNN for Scene Graph Generation
We propose a novel scene graph generation model called Graph R-CNN, that...
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03/27/2018
Neural Baby Talk
We introduce a novel framework for image captioning that can produce nat...
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06/05/2017
Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model
We present a novel training framework for neural sequence models, partic...
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03/05/2017
LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation
We present LR-GAN: an adversarial image generation model which takes sce...
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05/31/2016
Hierarchical Question-Image Co-Attention for Visual Question Answering
A number of recent works have proposed attention models for Visual Quest...
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04/13/2016
Joint Unsupervised Learning of Deep Representations and Image Clusters
In this paper, we propose a recurrent framework for Joint Unsupervised L...
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08/24/2014
