activity
20192023
most citedSemi-supervised Domain Adaptive Structure Learning

30 citations · 109 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2023★ 3 cited

Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection

Haichao Zhang, Can Qin, Yu Yin +1

Camouflaged objects that blend into natural scenes pose significant challenges for deep-learning models to detect and synthesize. While camouflaged object detection is a crucial ta…

cs.CV2022★ 1 cited

NeRFInvertor: High Fidelity NeRF-GAN Inversion for Single-shot Real Image Animation

Yu Yin, Kamran Ghasedi, HsiangTao Wu +3

Nerf-based Generative models have shown impressive capacity in generating high-quality images with consistent 3D geometry. Despite successful synthesis of fake identity images rand…

cs.CV2022★ 6 cited

Generating Topological Structure of Floorplans from Room Attributes

Yin Yu, Hutchcroft Will, Khosravan Naji +3

Analysis of indoor spaces requires topological information. In this paper, we propose to extract topological information from room attributes using what we call Iterative and adapt…

cs.CV2021★ 30 cited

Semi-supervised Domain Adaptive Structure Learning

Can Qin, Lichen Wang, Qianqian Ma +3

Semi-supervised domain adaptation (SSDA) is quite a challenging problem requiring methods to overcome both 1) overfitting towards poorly annotated data and 2) distribution shift ac…

cs.CV2020★ 9 cited

Collaborative Attention Mechanism for Multi-View Action Recognition

Yue Bai, Zhiqiang Tao, Lichen Wang +3

Multi-view action recognition (MVAR) leverages complementary temporal information from different views to improve the learning performance. Obtaining informative view-specific repr…

cs.CV2020★ 23 cited

Families In Wild Multimedia: A Multimodal Database for Recognizing Kinship

Joseph P. Robinson, Zaid Khan, Yu Yin +2

Kinship, a soft biometric detectable in media, is fundamental for a myriad of use-cases. Despite the difficulty of detecting kinship, annual data challenges using still-images have…

cs.CV2020★ 5 cited

Dual-Attention GAN for Large-Pose Face Frontalization

Yu Yin, Songyao Jiang, Joseph P. Robinson +1

Face frontalization provides an effective and efficient way for face data augmentation and further improves the face recognition performance in extreme pose scenario. Despite recen…

cs.CV2020★ 27 cited

Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge

Joseph P. Robinson, Yu Yin, Zaid Khan +7

Recognizing Families In the Wild (RFIW): an annual large-scale, multi-track automatic kinship recognition evaluation that supports various visual kin-based problems on scales much…

cs.CV2020★ 3 cited

Contradictory Structure Learning for Semi-supervised Domain Adaptation

Can Qin, Lichen Wang, Qianqian Ma +3

Current adversarial adaptation methods attempt to align the cross-domain features, whereas two challenges remain unsolved: 1) the conditional distribution mismatch and 2) the bias…

cs.CV2019★ 2 cited

Joint Super-Resolution and Alignment of Tiny Faces

Yu Yin, Joseph P. Robinson, Yulun Zhang +1

Super-resolution (SR) and landmark localization of tiny faces are highly correlated tasks. On the one hand, landmark localization could obtain higher accuracy with faces of high-re…