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Tianxiang Zheng

8 accepted papers

2026

Implicit Preference Alignment for Human Image Animation

ICML 2026poster

Human image animation has witnessed significant advancements, yet generating high-fidelity hand motions remains a persistent challenge due to their high degrees of freedom and motion complexity. While reinforcement learning from human feedback, particularly direct preference optimization, offers a p…

Cited by 0SourceScholar
2026

Phased One-Step Adversarial Equilibrium for Video Diffusion Models

AAAI 2026technical

Video diffusion generation suffers from critical sampling efficiency bottlenecks, particularly for large-scale models and long contexts. Existing video acceleration methods, adapted from image-based techniques, lack a single-step distillation ability for large-scale video models and task generalizat

Cited by 0SourcePDFScholar
2025

Wireless Powered Capsule Robots With a Wide Locomotion Range and Random Orientation via Planar Transmitting Coils

RA-L 2025

Capsule endoscopy and drug delivery hold great promise but are constrained by power supply limitations. This study introduces a battery-free capsule robot powered by wireless power transfer (WPT), utilizing a phase-controlled 2D planar array operating at 6.78 MHz. This setup provides a stable energy

Cited by 1SourceScholar
2025

Zero-Shot Blind-spot Image Denoising via Implicit Neural Sampling

CVPR 2025poster

The blind-spot principle has been a widely used tool in zero-shot image denoising but faces challenges with real-world noise that exhibits strong local correlations. Existing methods focus on reducing noise correlation, which also weaken the pixel correlations needed for accurately estimating missin…

Cited by 0SourcePDFScholar
2024

Pseudo-Siamese Blind-spot Transformers for Self-Supervised Real-World Denoising

NeurIPS 2024poster

Real-world image denoising remains a challenge task. This paper studies self-supervised image denoising, requiring only noisy images captured in a single shot. We revamping the blind-spot technique by leveraging the transformer’s capability for long-range pixel interactions, which is crucial for eff…

Cited by 0SourcePDFScholar
2022

BodyGAN: General-Purpose Controllable Neural Human Body Generation

CVPR 2022poster

Recent advances in generative adversarial networks (GANs) have provided potential solutions for photorealistic human image synthesis. However, the explicit and individual control of synthesis over multiple factors, such as poses, body shapes, and skin colors, remains difficult for existing methods.…

Cited by 11PDFScholar
2021

M3D-VTON: A Monocular-to-3D Virtual Try-On Network

ICCV 2021poster

Virtual 3D try-on can provide an intuitive and realistic view for online shopping and has a huge potential commercial value. However, existing 3D virtual try-on methods mainly rely on annotated 3D human shapes and garment templates, which hinders their applications in practical scenarios. 2D virtual…

Cited by 77PDFcodeScholar
2021

UltraPose: Synthesizing Dense Pose With 1 Billion Points by Human-Body Decoupling 3D Model

ICCV 2021poster

Recovering dense human poses from images plays a critical role in establishing an image-to-surface correspondence between RGB images and the 3D surface of the human body, serving the foundation of rich real-world applications, such as virtual humans, monocular-to-3d reconstruction. However, the popu…

Cited by 20PDFcodeScholar