114 citations · 475 across the 42 of their papers we have counts for
8 papers · 1 filter
Measuring Dataset Granularity
Yin Cui, Zeqi Gu, Dhruv Mahajan +3
Despite the increasing visibility of fine-grained recognition in our field, "fine-grained'' has thus far lacked a precise definition. In this work, building upon clustering theory,…
Unconstrained Facial Expression Transfer using Style-based Generator
Chao Yang, Ser-Nam Lim
Facial expression transfer and reenactment has been an important research problem given its applications in face editing, image manipulation, and fabricated videos generation. We p…
Unsupervised Deep Metric Learning via Auxiliary Rotation Loss
Xuefei Cao, Bor-Chun Chen, Ser-Nam Lim
Deep metric learning is an important area due to its applicability to many domains such as image retrieval and person re-identification. The main drawback of such models is the nec…
Fine-grained Synthesis of Unrestricted Adversarial Examples
Omid Poursaeed, Tianxing Jiang, Yordanos Goshu +3
We propose a novel approach for generating unrestricted adversarial examples by manipulating fine-grained aspects of image generation. Unlike existing unrestricted attacks that typ…
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors
Zuxuan Wu, Ser-Nam Lim, Larry Davis +1
We present a systematic study of adversarial attacks on state-of-the-art object detection frameworks. Using standard detection datasets, we train patterns that suppress the objectn…
Cross-X Learning for Fine-Grained Visual Categorization
Wei Luo, Xitong Yang, Xianjie Mo +5
Recognizing objects from subcategories with very subtle differences remains a challenging task due to the large intra-class and small inter-class variation. Recent work tackles thi…
Enhancing Adversarial Example Transferability with an Intermediate Level Attack
Qian Huang, Isay Katsman, Horace He +3
Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool trained models. Adversarial examples often exhibit black-box transfer, meaning that adversa…
Efficient Object Embedding for Spliced Image Retrieval
Bor-Chun Chen, Zuxuan Wu, Larry S. Davis +1
Detecting spliced images is one of the emerging challenges in computer vision. Unlike prior methods that focus on detecting low-level artifacts generated during the manipulation pr…