Papers
11,951 papers found
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Adrien Bardes, Jean Ponce, Yann LeCun
ViDT: An Efficient and Effective Fully Transformer-based Object Detector
Hwanjun Song, Deqing Sun, Sanghyuk Chun et al.
Vision-Based Manipulators Need to Also See from Their Hands
Kyle Hsu, Moo Jin Kim, Rafael Rafailov et al.
Visual Correspondence Hallucination
Hugo Germain, Vincent Lepetit, Guillaume Bourmaud
Visual hyperacuity with moving sensor and recurrent neural computations
Alexander Rivkind, Or Ram, Eldad Assa et al.
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain
Lukas Schott, Julius Von Kügelgen, Frederik Träuble et al.
Visual Representation Learning over Latent Domains
Lucas Deecke, Timothy Hospedales, Hakan Bilen
ViTGAN: Training GANs with Vision Transformers
Kwonjoon Lee, Huiwen Chang, Lu Jiang et al.
Vitruvion: A Generative Model of Parametric CAD Sketches
Ari Seff, Wenda Zhou, Nick Richardson et al.
VOS: Learning What You Don't Know by Virtual Outlier Synthesis
Xuefeng Du, Zhaoning Wang, Mu Cai et al.
Watch Me Speak: 2D Visualization of Human Mouth during Speech
C Siddarth, Sathvik Udupa, Prasanta Kumar Ghosh
W-CTC: a Connectionist Temporal Classification Loss with Wild Cards
Xingyu Cai, Jiahong Yuan, Yuchen Bian et al.
WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection
Liang Peng, Senbo Yan, Boxi Wu et al.
Weighted Training for Cross-Task Learning
Shuxiao Chen, Koby Crammer, Hangfeng He et al.
What Do We Mean by Generalization in Federated Learning?
Honglin Yuan, Warren Richard Morningstar, Lin Ning et al.
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework
Zhiyuan Li, Tianhao Wang, Sanjeev Arora
What Makes Better Augmentation Strategies? Augment Difficult but Not too Different
Jaehyung Kim, Dongyeop Kang, Sungsoo Ahn et al.
What’s Wrong with Deep Learning in Tree Search for Combinatorial Optimization
Maximilian Böther, Otto Kißig, Martin Taraz et al.
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Ziang Song, Song Mei, Yu Bai
When should agents explore?
Miruna Pislar, David Szepesvari, Georg Ostrovski et al.
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations
Xiangning Chen, Cho-Jui Hsieh, Boqing Gong
When, Why, and Which Pretrained GANs Are Useful?
Timofey Grigoryev, Andrey Voynov, Artem Babenko
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective
Luca Scimeca, Seong Joon Oh, Sanghyuk Chun et al.
Whisper: IoT in the TV White Space Spectrum
Tusher Chakraborty, Heping Shi, Zerina Kapetanovic et al.
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL
Yanchao Sun, Ruijie Zheng, Yongyuan Liang et al.