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20182022
most citedJoint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition

11 citations · 11 across the 2 of their papers we have counts for

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7 papers · 1 filter

cs.CV2022

Portmanteauing Features for Scene Text Recognition

Yew Lee Tan, Ernest Yu Kai Chew, Adams Wai-Kin Kong +2

Scene text images have different shapes and are subjected to various distortions, e.g. perspective distortions. To handle these challenges, the state-of-the-art methods rely on a r…

cs.CV202111 cited

Joint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition

Mei Chee Leong, Hui Li Tan, Haosong Zhang +3

Fine-grained human action recognition is a core research topic in computer vision. Inspired by the recently proposed hierarchy representation of fine-grained actions in FineGym and…

cs.CV2019

Variational Prototype Replays for Continual Learning

Mengmi Zhang, Tao Wang, Joo Hwee Lim +2

Continual learning refers to the ability to acquire and transfer knowledge without catastrophically forgetting what was previously learned. In this work, we consider \emph{few-shot…

cs.CV2019

Lift-the-flap: what, where and when for context reasoning

Mengmi Zhang, Claire Tseng, Karla Montejo +2

Context reasoning is critical in a wide variety of applications where current inputs need to be interpreted in the light of previous experience and knowledge. Both spatial and temp…

cs.CV2018

Egocentric Spatial Memory

Mengmi Zhang, Keng Teck Ma, Shih-Cheng Yen +3

Egocentric spatial memory (ESM) defines a memory system with encoding, storing, recognizing and recalling the spatial information about the environment from an egocentric perspecti…

cs.CV2018

Finding any Waldo: zero-shot invariant and efficient visual search

Mengmi Zhang, Jiashi Feng, Keng Teck Ma +3

Searching for a target object in a cluttered scene constitutes a fundamental challenge in daily vision. Visual search must be selective enough to discriminate the target from distr…