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Related papers: Novel Object Synthesis via Adaptive Text-Image Har…

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We propose a new paradigm to automatically generate training data with accurate labels at scale using the text-to-image synthesis frameworks (e.g., DALL-E, Stable Diffusion, etc.). The proposed approach1 decouples training data generation…

Computer Vision and Pattern Recognition · Computer Science 2023-09-13 Yunhao Ge , Jiashu Xu , Brian Nlong Zhao , Neel Joshi , Laurent Itti , Vibhav Vineet

Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Lingjun Zhang , Xinyuan Chen , Yaohui Wang , Yue Lu , Yu Qiao

We present a novel approach for single-image mesh texturing, which employs a diffusion model with judicious conditioning to seamlessly transfer an object's texture from a single RGB image to a given 3D mesh object. We do not assume that the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Sai Raj Kishore Perla , Yizhi Wang , Ali Mahdavi-Amiri , Hao Zhang

Repurposing pre-trained diffusion models has been proven to be effective for NVS. However, these methods are mostly limited to a single object; directly applying such methods to compositional multi-object scenarios yields inferior results,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Ruijie Lu , Yixin Chen , Junfeng Ni , Baoxiong Jia , Yu Liu , Diwen Wan , Gang Zeng , Siyuan Huang

Recent text-to-image (T2I) diffusion models show outstanding performance in generating high-quality images conditioned on textual prompts. However, they fail to semantically align the generated images with the prompts due to their limited…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Ruichen Wang , Zekang Chen , Chen Chen , Jian Ma , Haonan Lu , Xiaodong Lin

In this project, we address the issue of infidelity in text-to-image generation, particularly for actions involving multiple objects. For this we build on top of the CONFORM framework which uses Contrastive Learning to improve the accuracy…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Tianxiang Xia , Lin Xiao , Yannick Montorfani , Francesco Pavia , Enis Simsar , Thomas Hofmann

This paper presents a novel method to deal with the challenging task of generating photographic images conditioned on semantic image descriptions. Our method introduces accompanying hierarchical-nested adversarial objectives inside the…

Computer Vision and Pattern Recognition · Computer Science 2018-04-10 Zizhao Zhang , Yuanpu Xie , Lin Yang

Subject-driven image inpainting has recently gained prominence in image editing with the rapid advancement of diffusion models. Beyond image guidance, recent studies have explored incorporating text guidance to achieve identity-preserved…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Yicheng Yang , Pengxiang Li , Lu Zhang , Liqian Ma , Ping Hu , Siyu Du , Yunzhi Zhuge , Xu Jia , Huchuan Lu

Novel-View Human Action Synthesis aims to synthesize the movement of a body from a virtual viewpoint, given a video from a real viewpoint. We present a novel 3D reasoning to synthesize the target viewpoint. We first estimate the 3D mesh of…

Computer Vision and Pattern Recognition · Computer Science 2020-10-09 Mohamed Ilyes Lakhal , Davide Boscaini , Fabio Poiesi , Oswald Lanz , Andrea Cavallaro

In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner. We identify and address two key challenges: the unsatisfactory outcomes of direct…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Sisi Dai , Wenhao Li , Haowen Sun , Haibin Huang , Chongyang Ma , Hui Huang , Kai Xu , Ruizhen Hu

The text-to-image synthesis by diffusion models has recently shown remarkable performance in generating high-quality images. Although performs well for simple texts, the models may get confused when faced with complex texts that contain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Chang Yu , Junran Peng , Xiangyu Zhu , Zhaoxiang Zhang , Qi Tian , Zhen Lei

There has been tremendous progress in large-scale text-to-image synthesis driven by diffusion models enabling versatile downstream applications such as 3D object synthesis from texts, image editing, and customized generation. We present a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-05 Ting-Hsuan Liao , Songwei Ge , Yiran Xu , Yao-Chih Lee , Badour AlBahar , Jia-Bin Huang

Generating images from text involving complex and novel object arrangements remains a significant challenge for current text-to-image (T2I) models. Although prior layout-based methods improve object arrangements using spatial constraints…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Zeeshan Khan , Shizhe Chen , Cordelia Schmid

Driven by the scalable diffusion models trained on large-scale datasets, text-to-image synthesis methods have shown compelling results. However, these models still fail to precisely follow the text prompt involving multiple objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Quynh Phung , Songwei Ge , Jia-Bin Huang

Recent breakthroughs in diffusion models, multimodal pretraining, and efficient finetuning have led to an explosion of text-to-image generative models. Given human evaluation is expensive and difficult to scale, automated methods are…

Computer Vision and Pattern Recognition · Computer Science 2023-10-19 Dhruba Ghosh , Hanna Hajishirzi , Ludwig Schmidt

3D object detection aims to recover the 3D information of concerning objects and serves as the fundamental task of autonomous driving perception. Its performance greatly depends on the scale of labeled training data, yet it is costly to…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Shuai Zeng , Wenzhao Zheng , Jiwen Lu , Haibin Yan

We seek to give users precise control over diffusion-based image generation by modeling complex scenes as sequences of layers, which define the desired spatial arrangement and visual attributes of objects in the scene. Collage Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Vishnu Sarukkai , Linden Li , Arden Ma , Christopher Ré , Kayvon Fatahalian

In this work, we are dedicated to a new task, i.e., hand-object interaction image generation, which aims to conditionally generate the hand-object image under the given hand, object and their interaction status. This task is challenging and…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Hezhen Hu , Weilun Wang , Wengang Zhou , Houqiang Li

Scene text detection techniques have garnered significant attention due to their wide-ranging applications. However, existing methods have a high demand for training data, and obtaining accurate human annotations is labor-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Ling Fu , Zijie Wu , Yingying Zhu , Yuliang Liu , Xiang Bai

Image editing approaches with diffusion models have been rapidly developed, yet their applicability are subject to requirements such as specific editing types (e.g., foreground or background object editing, style transfer), multiple…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Yuming Qiao , Fanyi Wang , Jingwen Su , Yanhao Zhang , Yunjie Yu , Siyu Wu , Guo-Jun Qi