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Recent years have witnessed remarkable progress in 3D content generation. However, corresponding evaluation methods struggle to keep pace. Automatic approaches have proven challenging to align with human preferences, and the mixed…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Weitao Wang , Haoran Xu , Yuxiao Yang , Zhifang Liu , Jun Meng , Haoqian Wang

The rapid evolution of Large Language Models (LLMs) is predicated on the quality and diversity of post-training datasets. However, a critical dichotomy persists: while models are rigorously benchmarked, the data fueling them remains a black…

We present En3D, an enhanced generative scheme for sculpting high-quality 3D human avatars. Unlike previous works that rely on scarce 3D datasets or limited 2D collections with imbalanced viewing angles and imprecise pose priors, our…

Computer Vision and Pattern Recognition · Computer Science 2024-01-03 Yifang Men , Biwen Lei , Yuan Yao , Miaomiao Cui , Zhouhui Lian , Xuansong Xie

Objective visual quality assessment of 3D models is a fundamental issue in computer graphics. Quality assessment metrics may allow a wide range of processes to be guided and evaluated, such as level of detail creation, compression,…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Jinjiang Guo , Vincent Vidal , Irene Cheng , Anup Basu , Atilla Baskurt , Guillaume Lavoue

We review human evaluation practices in automatic, speech-driven 3D gesture generation and find a lack of standardisation and frequent use of flawed experimental setups. This leads to a situation where it is impossible to know how different…

Aligning large visual generative models with human feedback is often performed through pairwise preference optimization. While such approaches are conceptually simple, they fundamentally rely on annotated pairs, limiting scalability in…

Machine Learning · Computer Science 2026-05-07 Jinbin Bai , Yu Lei , Qingyu Shi , Aosong Feng , Yi Xin , Zhuoran Zhao , Fei Shen , Kaidong Yu , Jason Li

3D scene generation seeks to synthesize spatially structured, semantically meaningful, and photorealistic environments for applications such as immersive media, robotics, autonomous driving, and embodied AI. Early methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Beichen Wen , Haozhe Xie , Zhaoxi Chen , Fangzhou Hong , Ziwei Liu

Many important decisions in our everyday lives, such as authentication via biometric models, are made by Artificial Intelligence (AI) systems. These can be in poor alignment with human expectations, and testing them on clear-cut existing…

Human-Computer Interaction · Computer Science 2024-09-20 Lukas Mecke , Daniel Buschek , Uwe Gruenefeld , Florian Alt

Generating 3D scenes from human motion sequences supports numerous applications, including virtual reality and architectural design. However, previous auto-regression-based human-aware 3D scene generation methods have struggled to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Xiaolin Hong , Hongwei Yi , Fazhi He , Qiong Cao

While world models have emerged as a cornerstone of embodied intelligence by enabling agents to reason about environmental dynamics through action-conditioned prediction, their evaluation remains fragmented. Current evaluation of embodied…

Recent advancements in visual generative models have enabled high-quality image and video generation, opening diverse applications. However, evaluating these models often demands sampling hundreds or thousands of images or videos, making…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Fan Zhang , Shulin Tian , Ziqi Huang , Yu Qiao , Ziwei Liu

Evaluating text-to-image generation models requires alignment with human perception, yet existing human-centric metrics are constrained by limited data coverage, suboptimal feature extraction, and inefficient loss functions. To address…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Yuhang Ma , Yunhao Shui , Xiaoshi Wu , Keqiang Sun , Hongsheng Li

Reward Modeling is critical in evaluating and improving the generation of Large Language Models (LLMs). While numerous recent works have shown its feasibility in improving safety, helpfulness, reasoning, and instruction-following ability,…

Computation and Language · Computer Science 2025-11-13 Hanning Zhang , Juntong Song , Juno Zhu , Yuanhao Wu , Tong Zhang , Cheng Niu

As 3D Gaussian Splatting (3DGS) gains attention in immersive media and digital content creation, assessing the aesthetics of 3D scenes becomes important in helping creators build more visually compelling 3D content. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Chuanzhi Xu , Boyu Wei , Haoxian Zhou , Xuanhua Yin , Zihan Deng , Haodong Chen , Qiang Qu , Weidong Cai

Human emotion synthesis is a crucial aspect of affective computing. It involves using computational methods to mimic and convey human emotions through various modalities, with the goal of enabling more natural and effective human-computer…

Machine Learning · Computer Science 2024-12-11 Fei Ma , Yukan Li , Yifan Xie , Ying He , Yi Zhang , Hongwei Ren , Zhou Liu , Wei Yao , Fuji Ren , Fei Richard Yu , Shiguang Ni

The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the significant progress made in generative models, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Wenqing Wang , Haosen Yang , Josef Kittler , Xiatian Zhu

Generative Adversarial Networks (GANs) have emerged as powerful tools for high-quality image generation and real image editing by manipulating their latent spaces. Recent advancements in GANs include 3D-aware models such as EG3D, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Bahri Batuhan Bilecen , Yigit Yalin , Ning Yu , Aysegul Dundar

In contemporary architectural design, the growing complexity and diversity of design demands have made generative plugin tools essential for quickly producing initial concepts and exploring novel 3D forms. However, objectively analyzing the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Jun Yin , Jing Zhong , Pengyu Zeng , Peilin Li , Zixuan Dai , Miao Zhang , Shuai Lu

The recent advances in text and image synthesis show a great promise for the future of generative models in creative fields. However, a less explored area is the one of 3D model generation, with a lot of potential applications to game…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Antoine Schnepf , Flavian Vasile , Ugo Tanielian

3D content creation from text prompts has shown remarkable success recently. However, current text-to-3D methods often generate 3D results that do not align well with human preferences. In this paper, we present a comprehensive framework,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Junliang Ye , Fangfu Liu , Qixiu Li , Zhengyi Wang , Yikai Wang , Xinzhou Wang , Yueqi Duan , Jun Zhu