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06/14/2023
AssistGPT: A General Multi-modal Assistant that can Plan, Execute, Inspect, and Learn
Recent research on Large Language Models (LLMs) has led to remarkable ad...
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03/29/2023
MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks
The development of language models have moved from encoder-decoder to de...
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12/19/2022
MIST: Multi-modal Iterative Spatial-Temporal Transformer for Long-form Video Question Answering
To build Video Question Answering (VideoQA) systems capable of assisting...
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09/15/2022
OmniVL:One Foundation Model for Image-Language and Video-Language Tasks
This paper presents OmniVL, a new foundation model to support both image...
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07/26/2022
Learning Visual Representation from Modality-Shared Contrastive Language-Image Pre-training
Large-scale multi-modal contrastive pre-training has demonstrated great ...
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06/03/2022
Visual Clues: Bridging Vision and Language Foundations for Image Paragraph Captioning
People say, "A picture is worth a thousand words". Then how can we get t...
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05/22/2022
Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners
The goal of this work is to build flexible video-language models that ca...
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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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01/13/2022
CLIP-Event: Connecting Text and Images with Event Structures
Vision-language (V+L) pretraining models have achieved great success in ...
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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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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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06/08/2021
VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
Most existing video-and-language (VidL) research focuses on a single dat...
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04/01/2021
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training
Vision-and-language pre-training has achieved impressive success in lear...
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04/01/2021
CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning
This work concerns video-language pre-training and representation learni...
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02/11/2021
Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling
The canonical approach to video-and-language learning (e.g., video quest...
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01/12/2021
Temporally Guided Articulated Hand Pose Tracking in Surgical Videos
Articulated hand pose tracking is an underexplored problem that carries ...
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09/13/2020
Cluster-Former: Clustering-based Sparse Transformer for Long-Range Dependency Encoding
Transformer has become ubiquitous in the deep learning field. One of the...
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09/24/2019
Unified Vision-Language Pre-Training for Image Captioning and VQA
This paper presents a unified Vision-Language Pre-training (VLP) model. ...
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12/17/2018
Grounded Video Description
Video description is one of the most challenging problems in vision and ...
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12/13/2018
Dynamic Graph Modules for Modeling Higher-Order Interactions in Activity Recognition
Video action recognition, as a critical problem towards video understand...
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05/08/2018
Weakly-Supervised Video Object Grounding from Text by Loss Weighting and Object Interaction
We study weakly-supervised video object grounding: given a video segment...
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04/03/2018
End-to-End Dense Video Captioning with Masked Transformer
Dense video captioning aims to generate text descriptions for all events...
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03/28/2017
Towards Automatic Learning of Procedures from Web Instructional Videos
The potential for agents, whether embodied or software, to learn by obse...
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06/15/2016
Watch What You Just Said: Image Captioning with Text-Conditional Attention
Attention mechanisms have attracted considerable interest in image capti...
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08/21/2015
