no code implementations • 30 Apr 2024 • Yunhao Ge, Xiaohui Zeng, Jacob Samuel Huffman, Tsung-Yi Lin, Ming-Yu Liu, Yin Cui
VFC consists of three steps: 1) proposal, where image-to-text captioning models propose multiple initial captions; 2) verification, where a large language model (LLM) utilizes tools such as object detection and VQA models to fact-check proposed captions; 3) captioning, where an LLM generates the final caption by summarizing caption proposals and the fact check verification results.
no code implementations • 25 Apr 2024 • Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Chunyi Li, Tengchuan Kou, Wei Sun, HaoNing Wu, Yixuan Gao, Yuqin Cao, ZiCheng Zhang, Xiele Wu, Radu Timofte, Fei Peng, Huiyuan Fu, Anlong Ming, Chuanming Wang, Huadong Ma, Shuai He, Zifei Dou, Shu Chen, Huacong Zhang, Haiyi Xie, Chengwei Wang, Baoying Chen, Jishen Zeng, Jianquan Yang, Weigang Wang, Xi Fang, Xiaoxin Lv, Jun Yan, Tianwu Zhi, Yabin Zhang, Yaohui Li, Yang Li, Jingwen Xu, Jianzhao Liu, Yiting Liao, Junlin Li, Zihao Yu, Yiting Lu, Xin Li, Hossein Motamednia, S. Farhad Hosseini-Benvidi, Fengbin Guan, Ahmad Mahmoudi-Aznaveh, Azadeh Mansouri, Ganzorig Gankhuyag, Kihwan Yoon, Yifang Xu, Haotian Fan, Fangyuan Kong, Shiling Zhao, Weifeng Dong, Haibing Yin, Li Zhu, Zhiling Wang, Bingchen Huang, Avinab Saha, Sandeep Mishra, Shashank Gupta, Rajesh Sureddi, Oindrila Saha, Luigi Celona, Simone Bianco, Paolo Napoletano, Raimondo Schettini, Junfeng Yang, Jing Fu, Wei zhang, Wenzhi Cao, Limei Liu, Han Peng, Weijun Yuan, Zhan Li, Yihang Cheng, Yifan Deng, Haohui Li, Bowen Qu, Yao Li, Shuqing Luo, Shunzhou Wang, Wei Gao, Zihao Lu, Marcos V. Conde, Xinrui Wang, Zhibo Chen, Ruling Liao, Yan Ye, Qiulin Wang, Bing Li, Zhaokun Zhou, Miao Geng, Rui Chen, Xin Tao, Xiaoyu Liang, Shangkun Sun, Xingyuan Ma, Jiaze Li, Mengduo Yang, Haoran Xu, Jie zhou, Shiding Zhu, Bohan Yu, Pengfei Chen, Xinrui Xu, Jiabin Shen, Zhichao Duan, Erfan Asadi, Jiahe Liu, Qi Yan, Youran Qu, Xiaohui Zeng, Lele Wang, Renjie Liao
A total of 196 participants have registered in the video track.
no code implementations • 22 Mar 2024 • Kevin Xie, Jonathan Lorraine, Tianshi Cao, Jun Gao, James Lucas, Antonio Torralba, Sanja Fidler, Xiaohui Zeng
Recent text-to-3D generation approaches produce impressive 3D results but require time-consuming optimization that can take up to an hour per prompt.
no code implementations • 6 Dec 2023 • Xuanchi Ren, Jiahui Huang, Xiaohui Zeng, Ken Museth, Sanja Fidler, Francis Williams
In addition to unconditional generation, we show that our model can be used to solve a variety of tasks such as user-guided editing, scene completion from a single scan, and text-to-3D.
no code implementations • ICCV 2023 • Jonathan Lorraine, Kevin Xie, Xiaohui Zeng, Chen-Hsuan Lin, Towaki Takikawa, Nicholas Sharp, Tsung-Yi Lin, Ming-Yu Liu, Sanja Fidler, James Lucas
Text-to-3D modelling has seen exciting progress by combining generative text-to-image models with image-to-3D methods like Neural Radiance Fields.
1 code implementation • CVPR 2023 • Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin
DreamFusion has recently demonstrated the utility of a pre-trained text-to-image diffusion model to optimize Neural Radiance Fields (NeRF), achieving remarkable text-to-3D synthesis results.
Ranked #2 on Text to 3D on T$^3$Bench
2 code implementations • 12 Oct 2022 • Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis
To advance 3D DDMs and make them useful for digital artists, we require (i) high generation quality, (ii) flexibility for manipulation and applications such as conditional synthesis and shape interpolation, and (iii) the ability to output smooth surfaces or meshes.
Ranked #1 on Point Cloud Generation on ShapeNet Airplane
no code implementations • 5 Jul 2022 • Gary Leung, Jun Gao, Xiaohui Zeng, Sanja Fidler
HILA extends hierarchical vision transformer architectures by adding local connections between features of higher and lower levels to the backbone encoder.
1 code implementation • 25 Jun 2021 • Xiaohui Zeng, Raquel Urtasun, Richard Zemel, Sanja Fidler, Renjie Liao
1) We propose a non-parametric prior distribution over the appearance of image parts so that the latent variable ``what-to-draw'' per step becomes a categorical random variable.
no code implementations • ECCV 2020 • Bo-Wen Chen, Huan Ling, Xiaohui Zeng, Gao Jun, Ziyue Xu, Sanja Fidler
Our approach tolerates a modest amount of noise in the box placements, thus typically only a few clicks are needed to annotate tracked boxes to a sufficient accuracy.
1 code implementation • ICCV 2019 • Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun
In practice, it performs similarly to the Hungarian algorithm during inference.
2 code implementations • NAACL 2018 • Yu-Siang Wang, Chenxi Liu, Xiaohui Zeng, Alan Yuille
The scene graphs generated by our learned neural dependency parser achieve an F-score similarity of 49. 67% to ground truth graphs on our evaluation set, surpassing best previous approaches by 5%.
no code implementations • CVPR 2019 • Xiaohui Zeng, Chenxi Liu, Yu-Siang Wang, Weichao Qiu, Lingxi Xie, Yu-Wing Tai, Chi Keung Tang, Alan L. Yuille
Though image-space adversaries can be interpreted as per-pixel albedo change, we verify that they cannot be well explained along these physically meaningful dimensions, which often have a non-local effect.