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20242026
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cs.CV2026

MoE3D: A Mixture-of-Experts Module for 3D Reconstruction

Zichen Wang, Ang Cao, Liam J. Wang +1

We propose a simple yet effective approach to enhance the performance of feed-forward 3D reconstruction models. Existing methods often struggle near depth discontinuities, where st…

cs.CV20263 cited

PKI: Prior Knowledge-Infused Neural Network for Few-Shot Class-Incremental Learning

Kexin Baoa, Fanzhao Lin, Zichen Wang +3

Few-shot class-incremental learning (FSCIL) aims to continually adapt a model on a limited number of new-class examples, facing two well-known challenges: catastrophic forgetting a…

cs.CV2025

DreamSwapV: Mask-guided Subject Swapping for Any Customized Video Editing

Weitao Wang, Zichen Wang, Hongdeng Shen +6

With the rapid progress of video generation, demand for customized video editing is surging, where subject swapping constitutes a key component yet remains under-explored. Prevaili…

cs.CV2025

Toward Rich Video Human-Motion2D Generation

Ruihao Xi, Xuekuan Wang, Yongcheng Li +5

Generating realistic and controllable human motions, particularly those involving rich multi-character interactions, remains a significant challenge due to data scarcity and the co…

cs.CV2024

UMG-CLIP: A Unified Multi-Granularity Vision Generalist for Open-World Understanding

Bowen Shi, Peisen Zhao, Zichen Wang +8

Vision-language foundation models, represented by Contrastive Language-Image Pre-training (CLIP), have gained increasing attention for jointly understanding both vision and textual…

cs.CV2024

Real-Time Human Action Recognition on Embedded Platforms

Ruiqi Wang, Zichen Wang, Peiqi Gao +7

With advancements in computer vision and deep learning, video-based human action recognition (HAR) has become practical. However, due to the complexity of the computation pipeline,…