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09/20/2023
Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding
While most modern video understanding models operate on short-range clip...
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07/11/2023
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the Backbone
Video-language pre-training (VLP) has become increasingly important due ...
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06/02/2023
VisualGPTScore: Visio-Linguistic Reasoning with Multimodal Generative Pre-Training Scores
Vision-language models (VLMs) discriminatively pre-trained with contrast...
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05/23/2023
Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality
Contrastively trained vision-language models have achieved remarkable pr...
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03/31/2023
DIME-FM: DIstilling Multimodal and Efficient Foundation Models
Large Vision-Language Foundation Models (VLFM), such as CLIP, ALIGN and ...
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06/15/2022
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone
Vision-language (VL) pre-training has recently received considerable att...
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06/12/2022
GLIPv2: Unifying Localization and Vision-Language Understanding
We present GLIPv2, a grounded VL understanding model, that serves both l...
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06/07/2022
Detection Hub: Unifying Object Detection Datasets via Query Adaptation on Language Embedding
Leveraging large-scale data can introduce performance gains on many comp...
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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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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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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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05/12/2021
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
We propose a Multiscale Invertible Generative Network (MsIGN) and associ...
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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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01/16/2021
Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix
This work considers the out-of-distribution (OOD) prediction problem whe...
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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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12/13/2020
MiniVLM: A Smaller and Faster Vision-Language Model
Recent vision-language (VL) studies have shown remarkable progress by le...
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04/13/2020
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
Large-scale pre-training methods of learning cross-modal representations...
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03/16/2020
Object-Centric Image Generation from Layouts
Despite recent impressive results on single-object and single-domain ima...
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02/25/2020
Statistical Adaptive Stochastic Gradient Methods
We propose a statistical adaptive procedure called SALSA for automatical...
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10/30/2019
Understanding the Role of Momentum in Stochastic Gradient Methods
The use of momentum in stochastic gradient methods has become a widespre...
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09/21/2019
Using Statistics to Automate Stochastic Optimization
Despite the development of numerous adaptive optimizers, tuning the lear...
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09/04/2019
TIGEr: Text-to-Image Grounding for Image Caption Evaluation
This paper presents a new metric called TIGEr for the automatic evaluati...
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06/09/2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Recent works have shown the effectiveness of randomized smoothing as a s...
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02/27/2019
Object-driven Text-to-Image Synthesis via Adversarial Training
In this paper, we propose Object-driven Attentive Generative Adversarial...
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02/23/2019
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Verification of neural networks enables us to gauge their robustness aga...
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02/23/2019
A Convex Relaxation Barrier to Tight Robust Verification of Neural Networks
Verification of neural networks enables us to gauge their robustness aga...
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11/01/2018
A bird's-eye view on coherence, and a worm's-eye view on cohesion
Generating coherent and cohesive long-form texts is a challenging proble...
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10/28/2018
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications
The Jacobian matrix (or the gradient for single-output networks) is dire...
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05/21/2018
Turbo Learning for Captionbot and Drawingbot
We study in this paper the problems of both image captioning and text-to...
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11/28/2017
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
In this paper, we propose an Attentional Generative Adversarial Network ...
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11/07/2017