b'Zhuowen Tu'

research

∙ 09/01/2023

Object-Centric Multiple Object Tracking

Unsupervised object-centric learning methods allow the partitioning of s...

0 Zixu Zhao, et al. ∙

research

∙ 08/29/2023

Characterizing Learning Curves During Language Model Pre-Training: Learning, Forgetting, and Stability

How do language models learn to make predictions during pre-training? To...

0 Tyler A. Chang, et al. ∙

research

∙ 08/19/2023

BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions

Vision Language Models (VLMs), which extend Large Language Models (LLM) ...

0 Wenbo Hu, et al. ∙

research

∙ 07/16/2023

DocTr: Document Transformer for Structured Information Extraction in Documents

We present a new formulation for structured information extraction (SIE)...

0 Haofu Liao, et al. ∙

research

∙ 07/06/2023

Distilling Large Vision-Language Model with Out-of-Distribution Generalizability

Large vision-language models have achieved outstanding performance, but ...

0 Xuanlin Li, et al. ∙

research

∙ 05/11/2023

Musketeer (All for One, and One for All): A Generalist Vision-Language Model with Task Explanation Prompts

We present a sequence-to-sequence vision-language model whose parameters...

0 Zhaoyang Zhang, et al. ∙

research

∙ 04/13/2023

Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction

3D-aware image synthesis encompasses a variety of tasks, such as scene g...

1 Hansheng Chen, et al. ∙

research

∙ 04/13/2023

DiffusionRig: Learning Personalized Priors for Facial Appearance Editing

We address the problem of learning person-specific facial priors from a ...

0 Zheng Ding, et al. ∙

research

∙ 10/19/2022

On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning

Reinforcement Learning (RL) algorithms can solve challenging control pro...

0 Yifan Xu, et al. ∙

research

∙ 10/05/2022

Point Cloud Recognition with Position-to-Structure Attention Transformers

In this paper, we present Position-to-Structure Attention Transformers (...

0 Zheng Ding, et al. ∙

research

∙ 08/18/2022

Open-Vocabulary Panoptic Segmentation with MaskCLIP

In this paper, we tackle a new computer vision task, open-vocabulary pan...

0 Zheng Ding, et al. ∙

research

∙ 08/11/2022

Semi-supervised Vision Transformers at Scale

We study semi-supervised learning (SSL) for vision transformers (ViT), a...

27 Zhaowei Cai, et al. ∙

research

∙ 05/22/2022

The Geometry of Multilingual Language Model Representations

We assess how multilingual language models maintain a shared multilingua...

0 Tyler A. Chang, et al. ∙

research

∙ 04/12/2022

X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks

In this paper, we study the challenging instance-wise vision-language ta...

6 Zhaowei Cai, et al. ∙

research

∙ 04/05/2022

Text Spotting Transformers

In this paper, we present TExt Spotting TRansformers (TESTR), a generic ...

6 Xiang Zhang, et al. ∙

research

∙ 03/31/2022

MeMOT: Multi-Object Tracking with Memory

We propose an online tracking algorithm that performs the object detecti...

6 Jiarui Cai, et al. ∙

research

∙ 01/06/2022

Contrastive Neighborhood Alignment

We present Contrastive Neighborhood Alignment (CNA), a manifold learning...

14 Pengkai Zhu, et al. ∙

research

∙ 11/04/2021

Towards Panoptic 3D Parsing for Single Image in the Wild

Performing single image holistic understanding and 3D reconstruction is ...

2 Sainan Liu, et al. ∙

research

∙ 07/09/2021

ViTGAN: Training GANs with Vision Transformers

Recently, Vision Transformers (ViTs) have shown competitive performance ...

24 Kwonjoon Lee, et al. ∙

research

∙ 07/07/2021

Long Short-Term Transformer for Online Action Detection

In this paper, we present Long Short-term TRansformer (LSTR), a new temp...

18 Mingze Xu, et al. ∙

research

∙ 06/10/2021

Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models

In this paper, we detail the relationship between convolutions and self-...

0 Tyler A. Chang, et al. ∙

research

∙ 05/13/2021

Compatibility-aware Heterogeneous Visual Search

We tackle the problem of visual search under resource constraints. Exist...

11 Rahul Duggal, et al. ∙

research

∙ 05/05/2021

Visual Composite Set Detection Using Part-and-Sum Transformers

Computer vision applications such as visual relationship detection and h...

8 Qi Dong, et al. ∙

research

∙ 04/14/2021

Pose Recognition with Cascade Transformers

In this paper, we present a regression-based pose recognition method usi...

0 Ke Li, et al. ∙

research

∙ 04/13/2021

Co-Scale Conv-Attentional Image Transformers

In this paper, we present Co-scale conv-attentional image Transformers (...

0 Weijian Xu, et al. ∙

research

∙ 01/21/2021

Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning

We present a plug-in replacement for batch normalization (BN) called exp...

9 Zhaowei Cai, et al. ∙

research

∙ 01/06/2021

Line Segment Detection Using Transformers without Edges

In this paper, we present a holistically end-to-end algorithm for line s...

10 Yifan Xu, et al. ∙

research

∙ 11/19/2020

Dual Contradistinctive Generative Autoencoder

We present a new generative autoencoder model with dual contradistinctiv...

4 Gaurav Parmar, et al. ∙

research

∙ 08/18/2020

One-pixel Signature: Characterizing CNN Models for Backdoor Detection

We tackle the convolution neural networks (CNNs) backdoor detection prob...

0 Shanjiaoyang Huang, et al. ∙

research

∙ 04/02/2020

Guided Variational Autoencoder for Disentanglement Learning

We propose an algorithm, guided variational autoencoder (Guided-VAE), th...

9 Zheng Ding, et al. ∙

research

∙ 10/13/2019

Neural Program Synthesis By Self-Learning

Neural inductive program synthesis is a task generating instructions tha...

0 Yifan Xu, et al. ∙

research

∙ 10/13/2019

Rethinking Exposure Bias In Language Modeling

Exposure bias describes the phenomenon that a language model trained und...

0 Yifan Xu, et al. ∙

research

∙ 10/09/2019

Unaligned Image-to-Sequence Transformation with Loop Consistency

We tackle the problem of modeling sequential visual phenomena. Given exa...

25 Siyang Wang, et al. ∙

research

∙ 06/13/2019

Learning Instance Occlusion for Panoptic Segmentation

Recently, the vision community has shown renewed interest in the effort ...

4 Justin Lazarow, et al. ∙

research

∙ 03/19/2018

Local Binary Pattern Networks

Memory and computation efficient deep learning architec- tures are cruci...

0 Jeng-Hau Lin, et al. ∙

research

∙ 12/13/2017

Rethinking Spatiotemporal Feature Learning For Video Understanding

In this paper we study 3D convolutional networks for video understanding...

0 Saining Xie, et al. ∙

research

∙ 12/06/2017

Top-down Flow Transformer Networks

We study the deformation fields of feature maps across convolutional net...

0 Zhiwei Jia, et al. ∙

research

∙ 11/26/2017

DeepRadiologyNet: Radiologist Level Pathology Detection in CT Head Images

We describe a system to automatically filter clinically significant find...

0 Jameson Merkow, et al. ∙

research

∙ 11/24/2017

Wasserstein Introspective Neural Networks

We present Wasserstein introspective neural networks (WINN) that are bot...

0 Kwonjoon Lee, et al. ∙

research

∙ 07/15/2017

Binarized Convolutional Neural Networks with Separable Filters for Efficient Hardware Acceleration

State-of-the-art convolutional neural networks are enormously costly in ...

0 Jeng-Hau Lin, et al. ∙

research

∙ 04/25/2017

Introspective Generative Modeling: Decide Discriminatively

We study unsupervised learning by developing introspective generative mo...

0 Justin Lazarow, et al. ∙

research

∙ 04/25/2017

Introspective Classifier Learning: Empower Generatively

In this paper we propose introspective classifier learning (ICL) that em...

0 Long Jin, et al. ∙

research

∙ 11/28/2016

Object Detection Free Instance Segmentation With Labeling Transformations

Instance segmentation has attracted recent attention in computer vision ...

0 Long Jin, et al. ∙

research

∙ 11/23/2016

Deep Convolutional Neural Networks with Merge-and-Run Mappings

A deep residual network, built by stacking a sequence of residual blocks...

0 Liming Zhao, et al. ∙

research

∙ 11/16/2016

Aggregated Residual Transformations for Deep Neural Networks

We present a simple, highly modularized network architecture for image c...

0 Saining Xie, et al. ∙

research

∙ 11/15/2016

Deeply supervised salient object detection with short connections

Recent progress on saliency detection is substantial, benefiting mostly ...

0 Qibin Hou, et al. ∙

research

∙ 07/31/2016

Deep FisherNet for Object Classification

Despite the great success of convolutional neural networks (CNN) for the...

0 Peng Tang, et al. ∙

research

∙ 05/26/2016

Dense Volume-to-Volume Vascular Boundary Detection

In this work, we present a novel 3D-Convolutional Neural Network (CNN) a...

0 Jameson Merkow, et al. ∙

research

∙ 11/23/2015

What Happened to My Dog in That Network: Unraveling Top-down Generators in Convolutional Neural Networks

Top-down information plays a central role in human perception, but plays...

0 Patrick W. Gallagher, et al. ∙

research

∙ 09/30/2015

Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree

We seek to improve deep neural networks by generalizing the pooling oper...

0 Chen-Yu Lee, et al. ∙

Zhuowen Tu

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