In particular, each tuple consists of a pair of images and 4. 6 discriminative questions (as positive samples) and 5. 9 non-discriminative questions (as negative samples) on average.
We present a practical approach to address the problem of unconstrained face alignment for a single image.
Ranked #18 on Face Alignment on AFLW-19
We investigate the problem of fine-grained sketch-based image retrieval (SBIR), where free-hand human sketches are used as queries to perform instance-level retrieval of images.
Ranked #3 on Sketch-Based Image Retrieval on Chairs
In this paper, we propose deformable deep convolutional neural networks for generic object detection.
no code implementations • 11 Sep 2014 • Wanli Ouyang, Ping Luo, Xingyu Zeng, Shi Qiu, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Yuanjun Xiong, Chen Qian, Zhenyao Zhu, Ruohui Wang, Chen-Change Loy, Xiaogang Wang, Xiaoou Tang
In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty.