1 citations · 1 across the 15 of their papers we have counts for
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BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models
Fangyikang Wang, Hubery Yin, Yuejiang Dong +5
The inversion of diffusion model sampling, which aims to find the corresponding initial noise of a sample, plays a critical role in various tasks. Recently, several heuristic exact…
LW2G: Learning Whether to Grow for Prompt-based Continual Learning
Qian Feng, Da-wei Zhou, Hanbin Zhao +4
Recent Prompt-based Continual learning (PCL) has achieved remarkable performance with pre-trained models. These approaches expand a prompt pool by adding a new set of prompts while…
TextToucher: Fine-Grained Text-to-Touch Generation
Jiahang Tu, Hao Fu, Fengyu Yang +3
Tactile sensation plays a crucial role in the development of multi-modal large models and embodied intelligence. To collect tactile data with minimal cost as possible, a series of…
DriveDiTFit: Fine-tuning Diffusion Transformers for Autonomous Driving
Jiahang Tu, Wei Ji, Hanbin Zhao +3
In autonomous driving, deep models have shown remarkable performance across various visual perception tasks with the demand of high-quality and huge-diversity training datasets. Su…
NeuroBind: Towards Unified Multimodal Representations for Neural Signals
Fengyu Yang, Chao Feng, Daniel Wang +8
Understanding neural activity and information representation is crucial for advancing knowledge of brain function and cognition. Neural activity, measured through techniques like e…
PECTP: Parameter-Efficient Cross-Task Prompts for Incremental Vision Transformer
Qian Feng, Hanbin Zhao, Chao Zhang +4
Incremental Learning (IL) aims to learn deep models on sequential tasks continually, where each new task includes a batch of new classes and deep models have no access to task-ID i…
APISR: Anime Production Inspired Real-World Anime Super-Resolution
Boyang Wang, Fengyu Yang, Xihang Yu +2
While real-world anime super-resolution (SR) has gained increasing attention in the SR community, existing methods still adopt techniques from the photorealistic domain. In this pa…
Neural Sinkhorn Gradient Flow
Huminhao Zhu, Fangyikang Wang, Chao Zhang +2
Wasserstein Gradient Flows (WGF) with respect to specific functionals have been widely used in the machine learning literature. Recently, neural networks have been adopted to appro…