Search Results for author: Xuefeng Hu

Found 12 papers, 5 papers with code

SPAN: Spatial Pyramid Attention Network for Image Manipulation Localization

1 code implementation ECCV 2020 Xuefeng Hu, Zhihan Zhang, Zhenye Jiang, Syomantak Chaudhuri, Zhenheng Yang, Ram Nevatia

Tehchniques for manipulating images are advancing rapidly; while these are helpful for many useful tasks, they also pose a threat to society with their ability to create believable misinformation.

Image Manipulation Image Manipulation Detection +3

InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning

no code implementations19 Sep 2024 Xiaotian Han, Yiren Jian, Xuefeng Hu, Haogeng Liu, Yiqi Wang, Qihang Fan, Yuang Ai, Huaibo Huang, Ran He, Zhenheng Yang, Quanzeng You

Pre-training on large-scale, high-quality datasets is crucial for enhancing the reasoning capabilities of Large Language Models (LLMs), especially in specialized domains such as mathematics.

Math Mathematical Reasoning

BaFTA: Backprop-Free Test-Time Adaptation For Zero-Shot Vision-Language Models

no code implementations17 Jun 2024 Xuefeng Hu, Ke Zhang, Min Sun, Albert Chen, Cheng-Hao Kuo, Ram Nevatia

Large-scale pretrained vision-language models like CLIP have demonstrated remarkable zero-shot image classification capabilities across diverse domains.

Image Classification Online Clustering +2

Large Language Models are Good Prompt Learners for Low-Shot Image Classification

1 code implementation CVPR 2024 Zhaoheng Zheng, Jingmin Wei, Xuefeng Hu, Haidong Zhu, Ram Nevatia

Thus, we propose LLaMP, Large Language Models as Prompt learners, that produces adaptive prompts for the CLIP text encoder, establishing it as the connecting bridge.

Classification Few-Shot Image Classification +1

ReCLIP: Refine Contrastive Language Image Pre-Training with Source Free Domain Adaptation

1 code implementation4 Aug 2023 Xuefeng Hu, Ke Zhang, Lu Xia, Albert Chen, Jiajia Luo, Yuyin Sun, Ken Wang, Nan Qiao, Xiao Zeng, Min Sun, Cheng-Hao Kuo, Ram Nevatia

Large-scale Pre-Training Vision-Language Model such as CLIP has demonstrated outstanding performance in zero-shot classification, e. g. achieving 76. 3% top-1 accuracy on ImageNet without seeing any example, which leads to potential benefits to many tasks that have no labeled data.

Image Classification Language Modeling +3

Efficient Feature Distillation for Zero-shot Annotation Object Detection

2 code implementations21 Mar 2023 Zhuoming Liu, Xuefeng Hu, Ram Nevatia

We propose a new setting for detecting unseen objects called Zero-shot Annotation object Detection (ZAD).

Object object-detection +1

MixNorm: Test-Time Adaptation Through Online Normalization Estimation

no code implementations21 Oct 2021 Xuefeng Hu, Gokhan Uzunbas, Sirius Chen, Rui Wang, Ashish Shah, Ram Nevatia, Ser-Nam Lim

We present a simple and effective way to estimate the batch-norm statistics during test time, to fast adapt a source model to target test samples.

Test-time Adaptation Unsupervised Domain Adaptation +1

Testing-Time Adaptation through Online Normalization Estimation

no code implementations29 Sep 2021 Xuefeng Hu, Mustafa Uzunbas, Bor-Chun Chen, Rui Wang, Ashish Shah, Ram Nevatia, Ser-Nam Lim

We present a simple and effective way to estimate the batch-norm statistics during test time, to fast adapt a source model to target test samples.

Test-time Adaptation Unsupervised Domain Adaptation +1

SimMER: Simple Maximization of Entropy and Rank for Self-supervised Representation Learning

no code implementations29 Sep 2021 Zhengyu Yang, Zijian Hu, Xuefeng Hu, Ram Nevatia

With both entropy and rank maximization, our method surpasses the state-of-the-art on CIFAR-10 and Mini-ImageNet under the standard linear evaluation protocol.

Contrastive Learning Linear evaluation +2

SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification

1 code implementation CVPR 2021 Zijian Hu, Zhengyu Yang, Xuefeng Hu, Ram Nevatia

Combining the Pair Loss with the techniques developed by the MixMatch family, our proposed SimPLE algorithm shows significant performance gains over previous algorithms on CIFAR-100 and Mini-ImageNet, and is on par with the state-of-the-art methods on CIFAR-10 and SVHN.

Classification General Classification +3

SPAN: Spatial Pyramid Attention Network forImage Manipulation Localization

no code implementations1 Sep 2020 Xuefeng Hu, Zhihan Zhang, Zhenye Jiang, Syomantak Chaudhuri, Zhenheng Yang, Ram Nevatia

We present a novel framework, Spatial Pyramid Attention Network (SPAN) for detection and localization of multiple types of image manipulations.

Position

Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval

no code implementations4 Mar 2019 Svebor Karaman, Xudong Lin, Xuefeng Hu, Shih-Fu Chang

We propose an unsupervised hashing method which aims to produce binary codes that preserve the ranking induced by a real-valued representation.

Decoder Image Retrieval +2

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