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Bowen Tian

5 papers hereh-index 323 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
same name
  • Bowen Tian — 12 papers, h 3
  • Bowen Tian — 2 papers, h 1
  • Bowen Tian — 1 paper
  • Bowen Tian — 1 paper, h 4
  • Bowen Tian — 1 paper, h 4
  • Bowen Tian — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedANT: Adaptive Neural Temporal-Aware Text-to-Motion Model

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models

Haosen Li, Wenshuo Chen, Lei Wang +4

Diffusion models have achieved remarkable success in synthesizing complex static and temporal visuals, a breakthrough largely driven by Classifier-Free Guidance (CFG). However, des…

cs.CV2025

POLARIS: Projection-Orthogonal Least Squares for Robust and Adaptive Inversion in Diffusion Models

Wenshuo Chen, Haosen Li, Shaofeng Liang +6

The Inversion-Denoising Paradigm, which is based on diffusion models, excels in diverse image editing and restoration tasks. We revisit its mechanism and reveal a critical, overloo…

cs.CV2025

LUMA: Low-Dimension Unified Motion Alignment with Dual-Path Anchoring for Text-to-Motion Diffusion Model

Haozhe Jia, Wenshuo Chen, Yuqi Lin +8

While current diffusion-based models, typically built on U-Net architectures, have shown promising results on the text-to-motion generation task, they still suffer from semantic mi…

cs.CV2025★ 1 cited

ANT: Adaptive Neural Temporal-Aware Text-to-Motion Model

Wenshuo Chen, Kuimou Yu, Haozhe Jia +8

While diffusion models advance text-to-motion generation, their static semantic conditioning ignores temporal-frequency demands: early denoising requires structural semantics for m…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.