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Microsoft at CVPR 2024: Innovations in computer vision and AI research

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Exploring how context, culture, and character matter in avatar research

FeatUp: A Model-Agnostic Framework for Features at Any Resolution

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Published Date

Publication

Deep Incremental Hashing Network for Efficient Image Retrieval

Dayan Wu, Qi Dai, Jing Liu, Bo Li, Weiping Wang

CVPR | June 2019

Publication

Deformable ConvNets v2: More Deformable, Better Results

Xizhou Zhu, Han Hu, Stephen Lin, Jifeng Dai

Computer Vision and Pattern Recognition (CVPR) | June 2019

Publication

BAD SLAM: Bundle Adjusted Direct RGB-D SLAM

Thomas Maximilian Schöps, Torsten Sattler, Marc Pollefeys

2019 Conference on Computer Vision and Pattern Recognition (CVPR) | June 2019

Publication

Face Parsing with RoI Tanh-Warping

CVPR 2019 | June 2019

Publication

Learning Rich Image Region Representation for Visual Question Answering

Bei Liu, Zhicheng Huang, Zhaoyang Zeng, Zheyu Chen, Jianlong Fu

MSR-TR-2020-1 | June 2019

Published by Microsoft

CVPR 2019, VQA Workshop

Project

Publication

SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking

Guangting Wang, Chong Luo, Zhiwei Xiong, Wenjun Zeng

IEEE Conference on Computer Vision and Pattern Recognition | June 2019

Publication

Mask-Guided Portrait Editing With Conditional GANs

Shuyang Gu, Jianmin Bao, Hao Yang, Dong Chen, Fang Wen, Lu Yuan

2019 Computer Vision and Pattern Recognition | May 2019

Publication

Face Parsing With RoI Tanh-Warping

Jinpeng Lin, Hao Yang, Dong Chen, Ming Zeng, Fang Wen, Lu Yuan

2019 Computer Vision and Pattern Recognition | May 2019

Publication

Bidirectional Learning for Domain Adaptation of Semantic Segmentation

Yunsheng Li, Lu Yuan, Nuno Vasconcelos

2019 Computer Vision and Pattern Recognition | May 2019

Tool

North American Camera Trap Images

This data set contains 3.7M camera trap images from five locations across the United States, with species-level labels for 28 species. More information about this data set is available in the associated manuscript: Tabak, M.…

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Computer Vision

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