most citedID-Animator: Zero-Shot Identity-Preserving Human Video Generation

6 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Pest-Thinker: Learning to Think and Reason like Entomologists via Reinforcement Learning

Xueheng Li, Yu Wang, Tao Hu +6

Pest-induced crop losses pose a major threat to global food security and sustainable agricultural development. While recent advances in Multimodal Large Language Models (MLLMs) hav…

cs.LG2026

When Classes Evolve: A Benchmark and Framework for Stage-Aware Class-Incremental Learning

Zheng Zhang, Tao Hu, Xueheng Li +4

Class-Incremental Learning (CIL) aims to sequentially learn new classes while mitigating catastrophic forgetting of previously learned knowledge. Conventional CIL approaches implic…

cs.CV2024★ 1 cited

Shuffle Mamba: State Space Models with Random Shuffle for Multi-Modal Image Fusion

Ke Cao, Xuanhua He, Tao Hu +3

Multi-modal image fusion integrates complementary information from different modalities to produce enhanced and informative images. Although State-Space Models, such as Mamba, are…

cs.CV2024★ 6 cited

ID-Animator: Zero-Shot Identity-Preserving Human Video Generation

Xuanhua He, Quande Liu, Shengju Qian +5

Generating high-fidelity human video with specified identities has attracted significant attention in the content generation community. However, existing techniques struggle to str…

cs.CV2024★ 1 cited

Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain

Xuanhua He, Tao Hu, Guoli Wang +9

RAW to sRGB mapping, which aims to convert RAW images from smartphones into RGB form equivalent to that of Digital Single-Lens Reflex (DSLR) cameras, has become an important area o…