69 citations · 300 across the 25 of their papers we have counts for
17 papers · 1 filter
Branch-Centric Tokenization and Test-Time Augmentation for Skeleton Generation
Zhengyuan Li, Chuanyu Pan, Yuanming Hu +2
Automatic skeleton generation involves predicting both joint positions and skeletal connectivity. However, existing approaches struggle to encode branch structures into token seque…
Making Vision Transformers Truly Shift-Equivariant
Renan A. Rojas-Gomez, Teck-Yian Lim, Minh N. Do +1
For computer vision, Vision Transformers (ViTs) have become one of the go-to deep net architectures. Despite being inspired by Convolutional Neural Networks (CNNs), ViTs' output re…
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation
Haochen Wang, Xiaodan Du, Jiahao Li +2
A diffusion model learns to predict a vector field of gradients. We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through…
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks
Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing +2
We propose learnable polyphase sampling (LPS), a pair of learnable down/upsampling layers that enable truly shift-invariant and equivariant convolutional networks. LPS can be train…
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation
William Gao, April Wang, Gal Metzer +2
We present TetGAN, a convolutional neural network designed to generate tetrahedral meshes. We represent shapes using an irregular tetrahedral grid which encodes an occupancy and di…
Text-Free Learning of a Natural Language Interface for Pretrained Face Generators
Xiaodan Du, Raymond A. Yeh, Nicholas Kolkin +2
We propose Fast text2StyleGAN, a natural language interface that adapts pre-trained GANs for text-guided human face synthesis. Leveraging the recent advances in Contrastive Languag…
Adapting CLIP For Phrase Localization Without Further Training
Jiahao Li, Greg Shakhnarovich, Raymond A. Yeh
Supervised or weakly supervised methods for phrase localization (textual grounding) either rely on human annotations or some other supervised models, e.g., object detectors. Obtain…
Total Variation Optimization Layers for Computer Vision
Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren +1
Optimization within a layer of a deep-net has emerged as a new direction for deep-net layer design. However, there are two main challenges when applying these layers to computer vi…
Inverting Adversarially Robust Networks for Image Synthesis
Renan A. Rojas-Gomez, Raymond A. Yeh, Minh N. Do +1
Despite unconditional feature inversion being the foundation of many image synthesis applications, training an inverter demands a high computational budget, large decoding capacity…
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data
Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh +1
Extracting detailed 3D information of objects from video data is an important goal for holistic scene understanding. While recent methods have shown impressive results when reconst…
Chirality Nets for Human Pose Regression
Raymond A. Yeh, Yuan-Ting Hu, Alexander G. Schwing
We propose Chirality Nets, a family of deep nets that is equivariant to the "chirality transform," i.e., the transformation to create a chiral pair. Through parameter sharing, odd…
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection
Khoi-Nguyen C. Mac, Dhiraj Joshi, Raymond A. Yeh +3
Fine-grained action detection is an important task with numerous applications in robotics and human-computer interaction. Existing methods typically utilize a two-stage approach in…
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Raymond A. Yeh, Jinjun Xiong, Wen-mei W. Hwu +2
Textual grounding is an important but challenging task for human-computer interaction, robotics and knowledge mining. Existing algorithms generally formulate the task as selection…
Unsupervised Textual Grounding: Linking Words to Image Concepts
Raymond A. Yeh, Minh N. Do, Alexander G. Schwing
Textual grounding, i.e., linking words to objects in images, is a challenging but important task for robotics and human-computer interaction. Existing techniques benefit from recen…
Video Frame Synthesis using Deep Voxel Flow
Ziwei Liu, Raymond A. Yeh, Xiaoou Tang +2
We address the problem of synthesizing new video frames in an existing video, either in-between existing frames (interpolation), or subsequent to them (extrapolation). This problem…
Semantic Facial Expression Editing using Autoencoded Flow
Raymond Yeh, Ziwei Liu, Dan B Goldman +1
High-level manipulation of facial expressions in images --- such as changing a smile to a neutral expression --- is challenging because facial expression changes are highly non-lin…
Semantic Image Inpainting with Deep Generative Models
Raymond A. Yeh, Chen Chen, Teck Yian Lim +3
Semantic image inpainting is a challenging task where large missing regions have to be filled based on the available visual data. Existing methods which extract information from on…