Zobrazeno 1 - 10
of 27 041
pro vyhledávání: '"Yang ming An"'
Reproducing color-magnitude diagrams (CMDs) of star-resolved galaxies is one of the most precise methods for measuring the star formation history (SFH) of nearby galaxies back to the earliest time. The upcoming big data era poses challenges to the tr
Externí odkaz:
http://arxiv.org/abs/2410.12253
Nowadays transformer-based Large Language Models (LLM) for code generation tasks usually apply sampling and filtering pipelines. Due to the sparse reward problem in code generation tasks caused by one-token incorrectness, transformer-based models wil
Externí odkaz:
http://arxiv.org/abs/2410.12236
Autor:
Chen, Lichang, Hu, Hexiang, Zhang, Mingda, Chen, Yiwen, Wang, Zifeng, Li, Yandong, Shyam, Pranav, Zhou, Tianyi, Huang, Heng, Yang, Ming-Hsuan, Gong, Boqing
We introduce OmnixR, an evaluation suite designed to benchmark SoTA Omni-modality Language Models, such as GPT-4o and Gemini. Evaluating OLMs, which integrate multiple modalities such as text, vision, and audio, presents unique challenges. Particular
Externí odkaz:
http://arxiv.org/abs/2410.12219
Autor:
Li, Xirui, Herrmann, Charles, Chan, Kelvin C. K., Li, Yinxiao, Sun, Deqing, Ma, Chao, Yang, Ming-Hsuan
Recent progress in image generation has sparked research into controlling these models through condition signals, with various methods addressing specific challenges in conditional generation. Instead of proposing another specialized technique, we in
Externí odkaz:
http://arxiv.org/abs/2410.11439
Autor:
Huang, Hsin-Ping, Wang, Xinyi, Bitton, Yonatan, Taitelbaum, Hagai, Tomar, Gaurav Singh, Chang, Ming-Wei, Jia, Xuhui, Chan, Kelvin C. K., Hu, Hexiang, Su, Yu-Chuan, Yang, Ming-Hsuan
Recent advancements in text-to-image generation have significantly enhanced the quality of synthesized images. Despite this progress, evaluations predominantly focus on aesthetic appeal or alignment with text prompts. Consequently, there is limited u
Externí odkaz:
http://arxiv.org/abs/2410.11824
Autor:
Tan, Shuai, Gong, Biao, Wang, Xiang, Zhang, Shiwei, Zheng, Dandan, Zheng, Ruobing, Zheng, Kecheng, Chen, Jingdong, Yang, Ming
Character image animation, which generates high-quality videos from a reference image and target pose sequence, has seen significant progress in recent years. However, most existing methods only apply to human figures, which usually do not generalize
Externí odkaz:
http://arxiv.org/abs/2410.10306
3D meshes are widely used in computer vision and graphics for their efficiency in animation and minimal memory use, playing a crucial role in movies, games, AR, and VR. However, creating temporally consistent and realistic textures for mesh sequences
Externí odkaz:
http://arxiv.org/abs/2410.10821
Spatiotemporal predictive learning methods generally fall into two categories: recurrent-based approaches, which face challenges in parallelization and performance, and recurrent-free methods, which employ convolutional neural networks (CNNs) as enco
Externí odkaz:
http://arxiv.org/abs/2410.04733
Autor:
Zhang, Junyi, Herrmann, Charles, Hur, Junhwa, Jampani, Varun, Darrell, Trevor, Cole, Forrester, Sun, Deqing, Yang, Ming-Hsuan
Estimating geometry from dynamic scenes, where objects move and deform over time, remains a core challenge in computer vision. Current approaches often rely on multi-stage pipelines or global optimizations that decompose the problem into subtasks, li
Externí odkaz:
http://arxiv.org/abs/2410.03825
Dynamic and interactive traffic scenarios pose significant challenges for autonomous driving systems. Reinforcement learning (RL) offers a promising approach by enabling the exploration of driving policies beyond the constraints of pre-collected data
Externí odkaz:
http://arxiv.org/abs/2410.02253