14 citations · 69 across the 8 of their papers we have counts for
8 papers
SVIT: Scaling up Visual Instruction Tuning
Bo Zhao, Boya Wu, Muyang He +1
Thanks to the emerging of foundation models, the large language and vision models are integrated to acquire the multimodal ability of visual captioning, question answering, etc. Al…
Pushing the Limits of 3D Shape Generation at Scale
Yu Wang, Xuelin Qian, Jingyang Huo +3
We present a significant breakthrough in 3D shape generation by scaling it to unprecedented dimensions. Through the adaptation of the Auto-Regressive model and the utilization of l…
Attribute-guided image generation from layout
Ke Ma, Bo Zhao, Leonid Sigal
Recent approaches have achieved great success in image generation from structured inputs, e.g., semantic segmentation, scene graph or layout. Although these methods allow specifica…
DwNet: Dense warp-based network for pose-guided human video generation
Polina Zablotskaia, Aliaksandr Siarohin, Bo Zhao +1
Generation of realistic high-resolution videos of human subjects is a challenging and important task in computer vision. In this paper, we focus on human motion transfer - generati…
Image Generation from Layout
Bo Zhao, Lili Meng, Weidong Yin +1
Despite significant recent progress on generative models, controlled generation of images depicting multiple and complex object layouts is still a difficult problem. Among the core…
Interpretable Spatio-temporal Attention for Video Action Recognition
Lili Meng, Bo Zhao, Bo Chang +4
Inspired by the observation that humans are able to process videos efficiently by only paying attention where and when it is needed, we propose an interpretable and easy plug-in sp…
Modular Generative Adversarial Networks
Bo Zhao, Bo Chang, Zequn Jie +1
Existing methods for multi-domain image-to-image translation (or generation) attempt to directly map an input image (or a random vector) to an image in one of the output domains. H…
Left-Right Comparative Recurrent Model for Stereo Matching
Zequn Jie, Pengfei Wang, Yonggen Ling +4
Leveraging the disparity information from both left and right views is crucial for stereo disparity estimation. Left-right consistency check is an effective way to enhance the disp…