125 citations · 155 across the 14 of their papers we have counts for
14 papers
VibeFlow: Versatile Video Chroma-Lux Editing through Self-Supervised Learning
Yifan Li, Pei Cheng, Bin Fu +2
Video chroma-lux editing, which aims to modify illumination and color while preserving structural and temporal fidelity, remains a significant challenge. Existing methods typically…
Token Pruning for In-Context Generation in Diffusion Transformers
Junqing Lin, Xingyu Zheng, Pei Cheng +3
In-context generation significantly enhances Diffusion Transformers (DiTs) by enabling controllable image-to-image generation through reference examples. However, the resulting inp…
ReMix: Towards a Unified View of Consistent Character Generation and Editing
Benjia Zhou, Bin Fu, Pei Cheng +3
Recent advances in large-scale text-to-image diffusion models (e.g., FLUX.1) have greatly improved visual fidelity in consistent character generation and editing. However, existing…
X-Intelligence 3.0: Training and Evaluating Reasoning LLM for Semiconductor Display
Xiaolin Yan, Yangxing Liu, Jiazhang Zheng +53
Large language models (LLMs) have recently achieved significant advances in reasoning and demonstrated their advantages in solving challenging problems. Yet, their effectiveness in…
AppAgent v2: Advanced Agent for Flexible Mobile Interactions
Yanda Li, Chi Zhang, Wenjia Jiang +6
With the advancement of Multimodal Large Language Models (MLLM), LLM-driven visual agents are increasingly impacting software interfaces, particularly those with graphical user int…
LinguaLinker: Audio-Driven Portraits Animation with Implicit Facial Control Enhancement
Rui Zhang, Yixiao Fang, Zhengnan Lu +3
This study delves into the intricacies of synchronizing facial dynamics with multilingual audio inputs, focusing on the creation of visually compelling, time-synchronized animation…
ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
Xiwei Hu, Rui Wang, Yixiao Fang +3
Diffusion models have demonstrated remarkable performance in the domain of text-to-image generation. However, most widely used models still employ CLIP as their text encoder, which…
FaceStudio: Put Your Face Everywhere in Seconds
Yuxuan Yan, Chi Zhang, Rui Wang +5
This study investigates identity-preserving image synthesis, an intriguing task in image generation that seeks to maintain a subject's identity while adding a personalized, stylist…
Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation
Zibo Zhao, Wen Liu, Xin Chen +7
We present a novel alignment-before-generation approach to tackle the challenging task of generating general 3D shapes based on 2D images or texts. Directly learning a conditional…
Learning Variational Motion Prior for Video-based Motion Capture
Xin Chen, Zhuo Su, Lingbo Yang +4
Motion capture from a monocular video is fundamental and crucial for us humans to naturally experience and interact with each other in Virtual Reality (VR) and Augmented Reality (A…
Coordinates Are NOT Lonely -- Codebook Prior Helps Implicit Neural 3D Representations
Fukun Yin, Wen Liu, Zilong Huang +3
Implicit neural 3D representation has achieved impressive results in surface or scene reconstruction and novel view synthesis, which typically uses the coordinate-based multi-layer…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Shuffle Transformer with Feature Alignment for Video Face Parsing
Rui Zhang, Yang Han, Zilong Huang +4
This is a short technical report introducing the solution of the Team TCParser for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR…
Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer
Zilong Huang, Youcheng Ben, Guozhong Luo +3
Very recently, Window-based Transformers, which computed self-attention within non-overlapping local windows, demonstrated promising results on image classification, semantic segme…