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07/03/2023
UniFine: A Unified and Fine-grained Approach for Zero-shot Vision-Language Understanding
Vision-language tasks, such as VQA, SNLI-VE, and VCR are challenging bec...
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03/23/2023
CoBIT: A Contrastive Bi-directional Image-Text Generation Model
The field of vision and language has witnessed a proliferation of pre-tr...
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12/14/2022
Find Someone Who: Visual Commonsense Understanding in Human-Centric Grounding
From a visual scene containing multiple people, human is able to disting...
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11/10/2022
Understanding ME? Multimodal Evaluation for Fine-grained Visual Commonsense
Visual commonsense understanding requires Vision Language (VL) models to...
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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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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
SGEITL: Scene Graph Enhanced Image-Text Learning for Visual Commonsense Reasoning
Answering complex questions about images is an ambitious goal for machin...
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06/08/2021
Graph-MLP: Node Classification without Message Passing in Graph
Graph Neural Network (GNN) has been demonstrated its effectiveness in de...
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10/24/2020
Weakly-supervised VisualBERT: Pre-training without Parallel Images and Captions
Pre-trained contextual vision-and-language (V L) models have brought i...
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06/17/2020
Learning Visual Commonsense for Robust Scene Graph Generation
Scene graph generation models understand the scene through object and pr...
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04/07/2020
