activity
20202023
most citedDeep Multimodal Fusion by Channel Exchanging

118 citations · 207 across the 34 of their papers we have counts for

collaborators

37 papers

cs.AI2023

Measuring Acoustics with Collaborative Multiple Agents

Yinfeng Yu, Changan Chen, Lele Cao +2

As humans, we hear sound every second of our life. The sound we hear is often affected by the acoustics of the environment surrounding us. For example, a spacious hall leads to mor…

cs.CV2023

Root Pose Decomposition Towards Generic Non-rigid 3D Reconstruction with Monocular Videos

Yikai Wang, Yinpeng Dong, Fuchun Sun +1

This work focuses on the 3D reconstruction of non-rigid objects based on monocular RGB video sequences. Concretely, we aim at building high-fidelity models for generic object categ…

cs.LG2023★ 1 cited

Towards the Sparseness of Projection Head in Self-Supervised Learning

Zeen Song, Xingzhe Su, Jingyao Wang +3

In recent years, self-supervised learning (SSL) has emerged as a promising approach for extracting valuable representations from unlabeled data. One successful SSL method is contra…

cs.CV2023

A Dimensional Structure based Knowledge Distillation Method for Cross-Modal Learning

Lingyu Si, Hongwei Dong, Wenwen Qiang +5

Due to limitations in data quality, some essential visual tasks are difficult to perform independently. Introducing previously unavailable information to transfer informative dark…

cs.LG2023★ 21 cited

Structure-Aware DropEdge Towards Deep Graph Convolutional Networks

Jiaqi Han, Wenbing Huang, Yu Rong +3

It has been discovered that Graph Convolutional Networks (GCNs) encounter a remarkable drop in performance when multiple layers are piled up. The main factor that accounts for why…

cs.LG2023★ 3 cited

Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic

Tianying Ji, Yu Luo, Fuchun Sun +3

Learning high-quality -value functions plays a key role in the success of many modern off-policy deep reinforcement learning (RL) algorithms. Previous works primarily focus on a…