57 citations · 98 across the 16 of their papers we have counts for
16 papers
Invariant Training 2D-3D Joint Hard Samples for Few-Shot Point Cloud Recognition
Xuanyu Yi, Jiajun Deng, Qianru Sun +3
We tackle the data scarcity challenge in few-shot point cloud recognition of 3D objects by using a joint prediction from a conventional 3D model and a well-trained 2D model. Surpri…
Keyword-Aware Relative Spatio-Temporal Graph Networks for Video Question Answering
Yi Cheng, Hehe Fan, Dongyun Lin +3
The main challenge in video question answering (VideoQA) is to capture and understand the complex spatial and temporal relations between objects based on given questions. Existing…
An Overview of Challenges in Egocentric Text-Video Retrieval
Burak Satar, Hongyuan Zhu, Hanwang Zhang +1
Text-video retrieval contains various challenges, including biases coming from diverse sources. We highlight some of them supported by illustrations to open a discussion. Besides,…
Is Bio-Inspired Learning Better than Backprop? Benchmarking Bio Learning vs. Backprop
Manas Gupta, Sarthak Ketanbhai Modi, Hang Zhang +2
Bio-inspired learning has been gaining popularity recently given that Backpropagation (BP) is not considered biologically plausible. Many algorithms have been proposed in the liter…
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…
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition
Mei Chee Leong, Haosong Zhang, Hui Li Tan +2
Fine-grained action recognition is a challenging task in computer vision. As fine-grained datasets have small inter-class variations in spatial and temporal space, fine-grained act…