most citedSpecies196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition

2 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20241 cited

GhostRNN: Reducing State Redundancy in RNN with Cheap Operations

Hang Zhou, Xiaoxu Zheng, Yunhe Wang +3

Recurrent neural network (RNNs) that are capable of modeling long-distance dependencies are widely used in various speech tasks, eg., keyword spotting (KWS) and speech enhancement…

cs.CV2024

RegionDrag: Fast Region-Based Image Editing with Diffusion Models

Jingyi Lu, Xinghui Li, Kai Han

Point-drag-based image editing methods, like DragDiffusion, have attracted significant attention. However, point-drag-based approaches suffer from computational overhead and misint…

cs.CV20241 cited

A Survey on 3D Human Avatar Modeling -- From Reconstruction to Generation

Ruihe Wang, Yukang Cao, Kai Han +1

3D modeling has long been an important area in computer vision and computer graphics. Recently, thanks to the breakthroughs in neural representations and generative models, we witn…

cs.CV20241 cited

Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Jianyuan Guo, Hanting Chen, Chengcheng Wang +3

Recent advancements in large language models have sparked interest in their extraordinary and near-superhuman capabilities, leading researchers to explore methods for evaluating an…

cs.CV20232 cited

Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition

Wei He, Kai Han, Ying Nie +2

The development of foundation vision models has pushed the general visual recognition to a high level, but cannot well address the fine-grained recognition in specialized domain su…