8 citations · 17 across the 8 of their papers we have counts for
8 papers
Future Optical Flow Prediction Improves Robot Control & Video Generation
Kanchana Ranasinghe, Honglu Zhou, Yu Fang +7
Future motion representations, such as optical flow, offer immense value for control and generative tasks. However, forecasting generalizable spatially dense motion representations…
GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR
Bharat Singh, Viveka Kulharia, Luyu Yang +3
Multimodal synthetic data generation is crucial in domains such as autonomous driving, robotics, augmented/virtual reality, and retail. We propose a novel approach, GenMM, for join…
Are Dense Labels Always Necessary for 3D Object Detection from Point Cloud?
Chenqiang Gao, Chuandong Liu, Jun Shu +5
Current state-of-the-art (SOTA) 3D object detection methods often require a large amount of 3D bounding box annotations for training. However, collecting such large-scale densely-s…
Learning Semantic Correspondence with Sparse Annotations
Shuaiyi Huang, Luyu Yang, Bo He +3
Finding dense semantic correspondence is a fundamental problem in computer vision, which remains challenging in complex scenes due to background clutter, extreme intra-class variat…
Burn After Reading: Online Adaptation for Cross-domain Streaming Data
Luyu Yang, Mingfei Gao, Zeyuan Chen +3
In the context of online privacy, many methods propose complex privacy and security preserving measures to protect sensitive data. In this paper, we argue that: not storing any sen…
Curriculum Manager for Source Selection in Multi-Source Domain Adaptation
Luyu Yang, Yogesh Balaji, Ser-Nam Lim +1
The performance of Multi-Source Unsupervised Domain Adaptation depends significantly on the effectiveness of transfer from labeled source domain samples. In this paper, we proposed…