activity
20192022
most citedGenerating Topological Structure of Floorplans from Room Attributes

6 citations · 14 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20221 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.CV20226 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.CV2020

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.CV20205 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

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

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…