6 papers
Exo2EgoPose: Leveraging Exocentric Demonstrations for Vision-Language guided Egocentric 3D Hand Pose Forecasting
Zhaofeng Shi, Heqian Qiu, Lanxiao Wang +2
Perceiving multimodal cues and forecasting fine-grained actions from an egocentric (Ego) perspective is vital for applications like robot manipulation. However, previous studies ei…
SAVA-X: Ego-to-Exo Imitation Error Detection via Scene-Adaptive View Alignment and Bidirectional Cross View Fusion
Xiang Li, Heqian Qiu, Lanxiao Wang +4
Error detection is crucial in industrial training, healthcare, and assembly quality control. Most existing work assumes a single-view setting and cannot handle the practical case w…
EgoMe: A New Dataset and Challenge for Following Me via Egocentric View in Real World
Heqian Qiu, Zhaofeng Shi, Lanxiao Wang +3
In human imitation learning, the imitator typically take the egocentric view as a benchmark, naturally transferring behaviors observed from an exocentric view to their owns, which…
Modulating CNN Features with Pre-Trained ViT Representations for Open-Vocabulary Object Detection
Xiangyu Gao, Yu Dai, Benliu Qiu +3
Owing to large-scale image-text contrastive training, pre-trained vision language model (VLM) like CLIP shows superior open-vocabulary recognition ability. Most existing open-vocab…
Region Prompt Tuning: Fine-grained Scene Text Detection Utilizing Region Text Prompt
Xingtao Lin, Heqian Qiu, Lanxiao Wang +3
Recent advancements in prompt tuning have successfully adapted large-scale models like Contrastive Language-Image Pre-trained (CLIP) for downstream tasks such as scene text detecti…
Distribution-Level Memory Recall for Continual Learning: Preserving Knowledge and Avoiding Confusion
Shaoxu Cheng, Kanglei Geng, Chiyuan He +7
Continual Learning (CL) aims to enable Deep Neural Networks (DNNs) to learn new data without forgetting previously learned knowledge. The key to achieving this goal is to avoid con…