3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Towards Scale-Aware Full Surround Monodepth with Transformers
Yuchen Yang, Xinyi Wang, Dong Li +3
Full surround monodepth (FSM) methods can learn from multiple camera views simultaneously in a self-supervised manner to predict the scale-aware depth, which is more practical for…
cs.CL2024★ 3 cited
EDDA: A Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance Detection
Daijun Ding, Li Dong, Zhichao Huang +5
Stance detection aims to determine the attitude expressed in text towards a given target. Zero-shot stance detection (ZSSD) has emerged to classify stances towards unseen targets d…
cs.CV2024
UPDP: A Unified Progressive Depth Pruner for CNN and Vision Transformer
Ji Liu, Dehua Tang, Yuanxian Huang +9
Traditional channel-wise pruning methods by reducing network channels struggle to effectively prune efficient CNN models with depth-wise convolutional layers and certain efficient…