Hi! I'm Menglin Jia (贾梦霖 in Chinese, KMnP in chemical elements --"jia meng lin" is the mandarin pronunciation of those chemical elements), a research scientist at Meta. I obtained my Ph.D. in Information Science at Cornell University, advised by Claire Cardie and Serge Belongie. My research interest include fine-grained recognition using both visual and textual information.

Selected Publications

DIFT teaser

Emergent Correspondence from Image Diffusion

NeurIPS 2023

Luming Tang*, Menglin Jia*, Qianqian Wang*, Cheng Perng Phoo, Bharath Hariharan (*Equal contribution)

VPT teaser

Visual Prompt Tuning

ECCV 2022

Menglin Jia*, Luming Tang*, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, Ser-Nam Lim (*Equal contribution)

when in doubt teaser

Rethinking Nearest Neighbors for Visual Classification

2021

Menglin Jia, Bor-Chun Chen, Zuxuan Wu, Claire Cardie, Serge Belongie, Ser-Nam Lim

when in doubt teaser

When in Doubt: Improving Classification Performance with Alternating Normalization

Findings of EMNLP 2021

Featured in the kexue.fm from a probability theory's pespective

Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoav Artzi, Claire Cardie

Intentonomy teaser

Exploring Visual Engagement Signals for Representation Learning

ICCV 2021

Menglin Jia*, Zuxuan Wu*, Austin Reiter, Claire Cardie, Serge Belongie, Ser-Nam Lim (*Equal contribution)

Special thanks to Marseille who is featured in the teaser photo!

Intentonomy teaser

Intentonomy: a Dataset and Study towards Human Intent Understanding

CVPR 2021 (oral)

Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie, Ser-Nam Lim

Fashionpedia teaser

Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset

ECCV 2020 (oral)

Featured in the ECCV 2020 Daily and BEST OF ECCV

Menglin Jia*, Mengyun Shi*, Mikhail Sirotenko*, Yin Cui*, Claire Cardie, Bharath Hariharan, Hartwig Adam, Serge Belongie (*Equal contribution)

Intentonomy teaser

Deep Multi-Modal Sets

2019

Austin Reiter, Menglin Jia, Pu Yang, Ser-Nam Lim

Class Balanced Loss teaser

Class-Balanced Loss Based on Effective Number of Samples

CVPR 2019

Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, Serge Belongie