Pengchuan Zhang

research

∙ 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...

0 Mohamed Afham, et al. ∙

research

∙ 07/11/2023

EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the Backbone

Video-language pre-training (VLP) has become increasingly important due ...

0 Shraman Pramanick, et al. ∙

research

∙ 06/02/2023

VisualGPTScore: Visio-Linguistic Reasoning with Multimodal Generative Pre-Training Scores

Vision-language models (VLMs) discriminatively pre-trained with contrast...

0 Zhiqiu Lin, et al. ∙

research

∙ 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...

0 Harman Singh, et al. ∙

research

∙ 03/31/2023

DIME-FM: DIstilling Multimodal and Efficient Foundation Models

Large Vision-Language Foundation Models (VLFM), such as CLIP, ALIGN and ...

0 Ximeng Sun, et al. ∙

research

∙ 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...

13 Zi-Yi Dou, et al. ∙

research

∙ 06/12/2022

GLIPv2: Unifying Localization and Vision-Language Understanding

We present GLIPv2, a grounded VL understanding model, that serves both l...

10 Haotian Zhang, et al. ∙

research

∙ 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...

9 Lingchen Meng, et al. ∙

research

∙ 04/20/2022

K-LITE: Learning Transferable Visual Models with External Knowledge

Recent state-of-the-art computer vision systems are trained from natural...

3 Sheng Shen, et al. ∙

research

∙ 04/19/2022

ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

Learning visual representations from natural language supervision has re...

2 Chunyuan Li, et al. ∙

research

∙ 04/07/2022

Unified Contrastive Learning in Image-Text-Label Space

Visual recognition is recently learned via either supervised learning on...

20 Jianwei Yang, et al. ∙

research

∙ 03/29/2022

Parameter-efficient Fine-tuning for Vision Transformers

In computer vision, it has achieved great success in adapting large-scal...

2 Xuehai He, et al. ∙

research

∙ 12/16/2021

RegionCLIP: Region-based Language-Image Pretraining

Contrastive language-image pretraining (CLIP) using image-text pairs has...

2 Yiwu Zhong, et al. ∙

research

∙ 12/07/2021

Grounded Language-Image Pre-training

This paper presents a grounded language-image pre-training (GLIP) model ...

4 Liunian Harold Li, et al. ∙

research

∙ 11/22/2021

Florence: A New Foundation Model for Computer Vision

Automated visual understanding of our diverse and open world demands com...

4 Lu Yuan, et al. ∙

research

∙ 07/27/2021

Image Scene Graph Generation (SGG) Benchmark

There is a surge of interest in image scene graph generation (object, at...

1 Xiaotian Han, et al. ∙

research

∙ 07/01/2021

Focal Self-attention for Local-Global Interactions in Vision Transformers

Recently, Vision Transformer and its variants have shown great promise o...

4 Jianwei Yang, et al. ∙

research

∙ 06/17/2021

Efficient Self-supervised Vision Transformers for Representation Learning

This paper investigates two techniques for developing efficient self-sup...

5 Chunyuan Li, et al. ∙

research

∙ 05/12/2021

Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference

We propose a Multiscale Invertible Generative Network (MsIGN) and associ...

3 Shumao Zhang, et al. ∙

research

∙ 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...

9 Pengchuan Zhang, et al. ∙

research

∙ 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...

0 Ruocheng Guo, et al. ∙

research

∙ 01/02/2021

VinVL: Making Visual Representations Matter in Vision-Language Models

This paper presents a detailed study of improving visual representations...

10 Pengchuan Zhang, et al. ∙

research

∙ 12/13/2020

MiniVLM: A Smaller and Faster Vision-Language Model

Recent vision-language (VL) studies have shown remarkable progress by le...

1 Jianfeng Wang, et al. ∙

research

∙ 04/13/2020

Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

Large-scale pre-training methods of learning cross-modal representations...

7 Xiujun Li, et al. ∙

research

∙ 03/16/2020

Object-Centric Image Generation from Layouts

Despite recent impressive results on single-object and single-domain ima...

7 Tristan Sylvain, et al. ∙

research

∙ 02/25/2020

Statistical Adaptive Stochastic Gradient Methods

We propose a statistical adaptive procedure called SALSA for automatical...

0 Pengchuan Zhang, et al. ∙

research

∙ 10/30/2019

Understanding the Role of Momentum in Stochastic Gradient Methods

The use of momentum in stochastic gradient methods has become a widespre...

0 Igor Gitman, et al. ∙

research

∙ 09/21/2019

Using Statistics to Automate Stochastic Optimization

Despite the development of numerous adaptive optimizers, tuning the lear...

0 Hunter Lang, et al. ∙

research

∙ 09/04/2019

TIGEr: Text-to-Image Grounding for Image Caption Evaluation

This paper presents a new metric called TIGEr for the automatic evaluati...

0 Ming Jiang, et al. ∙

research

∙ 06/09/2019

Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

Recent works have shown the effectiveness of randomized smoothing as a s...

4 Hadi Salman, et al. ∙

research

∙ 02/27/2019

Object-driven Text-to-Image Synthesis via Adversarial Training

In this paper, we propose Object-driven Attentive Generative Adversarial...

6 Wenbo Li, et al. ∙

research

∙ 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...

0 Hadi Salman, et al. ∙

research

∙ 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...

0 Hadi Salman, et al. ∙

research

∙ 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...

0 Woon Sang Cho, et al. ∙

research

∙ 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...

0 Huan Zhang, et al. ∙

research

∙ 05/21/2018

Turbo Learning for Captionbot and Drawingbot

We study in this paper the problems of both image captioning and text-to...

0 Qiuyuan Huang, et al. ∙

research

∙ 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 ...

1 Tao Xu, et al. ∙

research

∙ 11/07/2017

On the Discrimination-Generalization Tradeoff in GANs

Generative adversarial training can be generally understood as minimizin...

0 Pengchuan Zhang, et al. ∙

Pengchuan Zhang

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