1 citations · 2 across the 9 of their papers we have counts for
12 papers
R-SLPR: Region-based Small-to-Large Point-cloud Registration with Contrastive Learning
Yusen Wan, Zeyuan Chen, Qianshi Zou +1
Point-cloud (PC) registration is fundamental to three-dimensional (3D) perception in robotic systems. However, classic registration algorithms falter when aligning a source PC cont…
Soft Tail-dropping for Adaptive Visual Tokenization
Zeyuan Chen, Kai Zhang, Zhuowen Tu +1
We present Soft Tail-dropping Adaptive Tokenizer (STAT), a 1D discrete visual tokenizer that adaptively chooses the number of output tokens per image according to its structural co…
CVP: Central-Peripheral Vision-Inspired Multimodal Model for Spatial Reasoning
Zeyuan Chen, Xiang Zhang, Haiyang Xu +2
We present a central-peripheral vision-inspired framework (CVP), a simple yet effective multimodal model for spatial reasoning that draws inspiration from the two types of human vi…
Gaussian Swaying: Surface-Based Framework for Aerodynamic Simulation with 3D Gaussians
Hongru Yan, Xiang Zhang, Zeyuan Chen +2
Branches swaying in the breeze, flags rippling in the wind, and boats rocking on the water all show how aerodynamics shape natural motion -- an effect crucial for realism in vision…
C3Editor: Achieving Controllable Consistency in 2D Model for 3D Editing
Zeng Tao, Zheng Ding, Zeyuan Chen +3
Existing 2D-lifting-based 3D editing methods often encounter challenges related to inconsistency, stemming from the lack of view-consistent 2D editing models and the difficulty of…
OverLayBench: A Benchmark for Layout-to-Image Generation with Dense Overlaps
Bingnan Li, Chen-Yu Wang, Haiyang Xu +7
Despite steady progress in layout-to-image generation, current methods still struggle with layouts containing significant overlap between bounding boxes. We identify two primary ch…
Exploring the Equivalence of Closed-Set Generative and Real Data Augmentation in Image Classification
Haowen Wang, Guowei Zhang, Xiang Zhang +4
In this paper, we address a key scientific problem in machine learning: Given a training set for an image classification task, can we train a generative model on this dataset to en…
YOLO-Count: Differentiable Object Counting for Text-to-Image Generation
Guanning Zeng, Xiang Zhang, Zirui Wang +4
We propose YOLO-Count, a differentiable open-vocabulary object counting model that tackles both general counting challenges and enables precise quantity control for text-to-image (…
DepR: Depth Guided Single-view Scene Reconstruction with Instance-level Diffusion
Qingcheng Zhao, Xiang Zhang, Haiyang Xu +4
We propose DepR, a depth-guided single-view scene reconstruction framework that integrates instance-level diffusion within a compositional paradigm. Instead of reconstructing the e…
OmniControlNet: Dual-stage Integration for Conditional Image Generation
Yilin Wang, Haiyang Xu, Xiang Zhang +4
We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating i…
Bayesian Diffusion Models for 3D Shape Reconstruction
Haiyang Xu, Yu Lei, Zeyuan Chen +4
We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-u…
Dolfin: Diffusion Layout Transformers without Autoencoder
Yilin Wang, Zeyuan Chen, Liangjun Zhong +3
In this paper, we introduce a novel generative model, Diffusion Layout Transformers without Autoencoder (Dolfin), which significantly improves the modeling capability with reduced…