no code implementations • 6 Dec 2024 • Yibin Wang, Zhiyu Tan, Junyan Wang, Xiaomeng Yang, Cheng Jin, Hao Li
Based on this, we train a reward model LiFT-Critic to learn reward function effectively, which serves as a proxy for human judgment, measuring the alignment between given videos and human expectations.
no code implementations • CVPR 2024 • Junyan Wang, Zhenhong Sun, Zhiyu Tan, Xuanbai Chen, Weihua Chen, Hao Li, Cheng Zhang, Yang song
Vanilla text-to-image diffusion models struggle with generating accurate human images, commonly resulting in imperfect anatomies such as unnatural postures or disproportionate limbs. Existing methods address this issue mostly by fine-tuning the model with extra images or adding additional controls -- human-centric priors such as pose or depth maps -- during the image generation phase.
1 code implementation • 5 Mar 2023 • Junyan Wang, Zhenhong Sun, Yichen Qian, Dong Gong, Xiuyu Sun, Ming Lin, Maurice Pagnucco, Yang song
In this work, we propose to automatically design efficient 3D CNN architectures via a novel training-free neural architecture search approach tailored for 3D CNNs considering the model complexity.
Ranked #84 on
Action Recognition
on Something-Something V2
1 code implementation • Conference on Neural Information Processing Systems 2022 • Zhenhong Sun, Ce Ge, Junyan Wang, Ming Lin, Hesen Chen, Hao Li, Xiuyu Sun
Deploying deep convolutional neural networks on Internet-of-Things (IoT) devices is challenging due to the limited computational resources, such as limited SRAM memory and Flash storage.
1 code implementation • 23 Feb 2022 • Rui Gao, Fan Wan, Daniel Organisciak, Jiyao Pu, Junyan Wang, Haoran Duan, Peng Zhang, Xingsong Hou, Yang Long
Considering the increasing concerns about data copyright and privacy issues, we present a novel Absolute Zero-Shot Learning (AZSL) paradigm, i. e., training a classifier with zero real data.
2 code implementations • ICLR 2022 • Yiqi Jiang, Zhiyu Tan, Junyan Wang, Xiuyu Sun, Ming Lin, Hao Li
This heavy-backbone design paradigm is mostly due to the historical legacy when transferring image recognition models to object detection rather than an end-to-end optimized design for object detection.
no code implementations • 2 Sep 2021 • Nan Xu, Junyan Wang, Yuan Tian, Ruike Zhang, Wenji Mao
Thus researchers study the definition of cross-modal correlation category and construct various classification systems and predictive models.
1 code implementation • 8 Aug 2021 • Yang Bai, Junyan Wang, Yang Long, Bingzhang Hu, Yang song, Maurice Pagnucco, Yu Guan
Video captioning aims to automatically generate natural language sentences that can describe the visual contents of a given video.
no code implementations • 19 Aug 2020 • Junyan Wang, Yang Bai, Yang Long, Bingzhang Hu, Zhenhua Chai, Yu Guan, Xiaolin Wei
Video summarization aims to select representative frames to retain high-level information, which is usually solved by predicting the segment-wise importance score via a softmax function.
Ranked #5 on
Supervised Video Summarization
on SumMe
1 code implementation • 20 Jul 2019 • Junyan Wang, Bingzhang Hu, Yang Long, Yu Guan
Predicting future frames in natural video sequences is a new challenge that is receiving increasing attention in the computer vision community.
no code implementations • 16 Feb 2016 • Junyan Wang, Sai-Kit Yeung, Jue Wang, Kun Zhou
Comprehensive experiments on both RGB and RGB-D data demonstrate that our simple and effective method significantly outperforms the segmentation propagation methods adopted in the state-of-the-art video cutout systems, and the results also suggest the potential usefulness of our method in image cutout system.
no code implementations • 23 Mar 2015 • Junyan Wang, Sai-Kit Yeung
Superpixels have become prevalent in computer vision.
no code implementations • 29 Dec 2014 • Junyan Wang, Kap-Luk Chan
Our idea is to use general model of shape deformation in minimizing active contour energies.
no code implementations • 9 Apr 2014 • Junyan Wang, Sai-Kit Yeung
We propose a novel compact linear programming (LP) relaxation for binary sub-modular MRF in the context of object segmentation.
no code implementations • 24 Jul 2013 • Junyan Wang, Kap Luk Chan
To this effect, we obtain a mathematical model of interior points to boundary contour such that matching of interior feature points gives contour alignment, and we formulate the matching score as a constraint to active contour model such that the feature matching of maximum score that gives the contour alignment provides the initial feasible solution to the constrained optimization model of segmentation.