22 citations · 35 across the 8 of their papers we have counts for
9 papers
AssemblyHands: Towards Egocentric Activity Understanding via 3D Hand Pose Estimation
Takehiko Ohkawa, Kun He, Fadime Sener +3
We present AssemblyHands, a large-scale benchmark dataset with accurate 3D hand pose annotations, to facilitate the study of egocentric activities with challenging hand-object inte…
Adaptive Multi-Neighborhood Attention based Transformer for Graph Representation Learning
Gaichao Li, Jinsong Chen, Kun He
By incorporating the graph structural information into Transformers, graph Transformers have exhibited promising performance for graph representation learning in recent years. Exis…
Generating Pseudo-labels Adaptively for Few-shot Model-Agnostic Meta-Learning
Guodong Liu, Tongling Wang, Shuoxi Zhang +1
Model-Agnostic Meta-Learning (MAML) is a famous few-shot learning method that has inspired many follow-up efforts, such as ANIL and BOIL. However, as an inductive method, MAML is u…
NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
Jinsong Chen, Kaiyuan Gao, Gaichao Li +1
The graph Transformer emerges as a new architecture and has shown superior performance on various graph mining tasks. In this work, we observe that existing graph Transformers trea…
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural Activities
Fadime Sener, Dibyadip Chatterjee, Daniel Shelepov +4
Assembly101 is a new procedural activity dataset featuring 4321 videos of people assembling and disassembling 101 "take-apart" toy vehicles. Participants work without fixed instruc…
Adaptive Channel Allocation for Robust Differentiable Architecture Search
Chao Li, Jia Ning, Han Hu +1
Differentiable ARchiTecture Search (DARTS) has attracted much attention due to its simplicity and significant improvement in efficiency. However, the excessive accumulation of the…
Rethinking the Data Annotation Process for Multi-view 3D Pose Estimation with Active Learning and Self-Training
Qi Feng, Kun He, He Wen +2
Pose estimation of the human body and hands is a fundamental problem in computer vision, and learning-based solutions require a large amount of annotated data. In this work, we imp…
TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting
Haohai Sun, Jialun Zhong, Yunpu Ma +2
Temporal knowledge graph (TKG) reasoning is a crucial task that has gained increasing research interest in recent years. Most existing methods focus on reasoning at past timestamps…
Hashing with Mutual Information
Fatih Cakir, Kun He, Sarah Adel Bargal +1
Binary vector embeddings enable fast nearest neighbor retrieval in large databases of high-dimensional objects, and play an important role in many practical applications, such as i…