7 citations · 13 across the 6 of their papers we have counts for
8 papers · 1 filter
Kirin: Animal Motion Generation from In-the-Wild Video
Brian Nlong Zhao, Zhuoyang Pan, James M. Rehg +2
Understanding animal motion is fundamental to modeling animal behavior and biomechanics, yet progress in this area lags far behind human motion research due to the scarcity of high…
ST-DiffEye: Diffusion-based Continuous Gaze Generation via Joint Scanpath-Trajectory Modeling
Brian Nlong Zhao, Ozgur Kara, Junho Kim +1
We study the problem of human gaze modeling, which aims to generate the gaze patterns a viewer produces while observing a visual stimulus. Gaze is primarily captured through two mo…
Web-Scale Collection of Video Data for 4D Animal Reconstruction
Brian Nlong Zhao, Jiajun Wu, Shangzhe Wu
Computer vision for animals holds great promise for wildlife research but often depends on large-scale data, while existing collection methods rely on controlled capture setups. Re…
Probabilistic Prompt Distribution Learning for Animal Pose Estimation
Jiyong Rao, Brian Nlong Zhao, Yu Wang
Multi-species animal pose estimation has emerged as a challenging yet critical task, hindered by substantial visual diversity and uncertainty. This paper challenges the problem by…
DreamDistribution: Learning Prompt Distribution for Diverse In-distribution Generation
Brian Nlong Zhao, Yuhang Xiao, Jiashu Xu +6
The popularization of Text-to-Image (T2I) diffusion models enables the generation of high-quality images from text descriptions. However, generating diverse customized images with…
Beyond Generation: Harnessing Text to Image Models for Object Detection and Segmentation
Yunhao Ge, Jiashu Xu, Brian Nlong Zhao +3
We propose a new paradigm to automatically generate training data with accurate labels at scale using the text-to-image synthesis frameworks (e.g., DALL-E, Stable Diffusion, etc.).…
EM-Paste: EM-guided Cut-Paste with DALL-E Augmentation for Image-level Weakly Supervised Instance Segmentation
Yunhao Ge, Jiashu Xu, Brian Nlong Zhao +2
We propose EM-PASTE: an Expectation Maximization(EM) guided Cut-Paste compositional dataset augmentation approach for weakly-supervised instance segmentation using only image-level…
DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection
Yunhao Ge, Jiashu Xu, Brian Nlong Zhao +3
We propose a new paradigm to automatically generate training data with accurate labels at scale using the text-toimage synthesis frameworks (e.g., DALL-E, Stable Diffusion, etc.).…