Search Results for author: Bor-Chun Chen

Found 8 papers, 2 papers with code

Visual Prompt Tuning

no code implementations23 Mar 2022 Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, Ser-Nam Lim

The current modus operandi in adapting pre-trained models involves updating all the backbone parameters, ie, full fine-tuning.

Rethinking Nearest Neighbors for Visual Classification

1 code implementation15 Dec 2021 Menglin Jia, Bor-Chun Chen, Zuxuan Wu, Claire Cardie, Serge Belongie, Ser-Nam Lim

In this paper, we investigate $k$-Nearest-Neighbor (k-NN) classifiers, a classical model-free learning method from the pre-deep learning era, as an augmentation to modern neural network based approaches.


AdaViT: Adaptive Vision Transformers for Efficient Image Recognition

no code implementations30 Nov 2021 Lingchen Meng, Hengduo Li, Bor-Chun Chen, Shiyi Lan, Zuxuan Wu, Yu-Gang Jiang, Ser-Nam Lim

To this end, we introduce AdaViT, an adaptive computation framework that learns to derive usage policies on which patches, self-attention heads and transformer blocks to use throughout the backbone on a per-input basis, aiming to improve inference efficiency of vision transformers with a minimal drop of accuracy for image recognition.

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.

Unsupervised Domain Adaptation Zero-Shot Learning

Unsupervised Deep Metric Learning via Auxiliary Rotation Loss

no code implementations16 Nov 2019 Xuefei Cao, Bor-Chun Chen, Ser-Nam Lim

In this work, we propose to generate pseudo-labels for deep metric learning directly from clustering assignment and we introduce unsupervised deep metric learning (UDML) regularized by a self-supervision (SS) task.

Image Retrieval Metric Learning +1

Toward Realistic Image Compositing With Adversarial Learning

no code implementations CVPR 2019 Bor-Chun Chen, Andrew Kae

Compositing a realistic image is a challenging task and usually requires considerable human supervision using professional image editing software.

Generate, Segment and Refine: Towards Generic Manipulation Segmentation

1 code implementation24 Nov 2018 Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser Nam Lim, Larry S. Davis

The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being shared on the internet.

Detecting Image Manipulation Image Generation +3

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