Implicit Sparse Code Hashing. - Tsung-Yu Lin; Tsung-Wei Ke; Tyng-Luh Liu (CoRR, 2015)

Variational Convolutional Networks for Human-Centric Annotations. - Tsung-Wei Ke; Che-Wei Lin; Tyng-Luh Liu; Davi Geiger (ACCV (4), 2016)

Recursive reduction net for large-scale high-dimensional data. - Tsung-Wei Ke; Tyng-Luh Liu (ICIP, 2016)

Neural Multigrid. - Tsung-Wei Ke; Michael Maire; Stella X. Yu (CoRR, 2016)

Multigrid Neural Architectures. - Tsung-Wei Ke; Michael Maire; Stella X. Yu (CVPR, 2017)

Mooney face classification and prediction by learning across tone. - Tsung-Wei Ke; Stella X. Yu; David Whitney (ICIP, 2017)

Adaptive Affinity Fields for Semantic Segmentation. - Tsung-Wei Ke; Jyh-Jing Hwang; Ziwei Liu 002; Stella X. Yu (ECCV (1), 2018)

Adaptive Affinity Field for Semantic Segmentation. - Tsung-Wei Ke; Jyh-Jing Hwang; Ziwei Liu 002; Stella X. Yu (CoRR, 2018)

Adversarial Structure Matching Loss for Image Segmentation. - Jyh-Jing Hwang; Tsung-Wei Ke; Jianbo Shi; Stella X. Yu (CoRR, 2018)

Adversarial Structure Matching for Structured Prediction Tasks. - Jyh-Jing Hwang; Tsung-Wei Ke; Jianbo Shi; Stella X. Yu (CVPR, 2019)

Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning. - Tsung-Wei Ke; Jyh-Jing Hwang; Stella X. Yu (ICLR, 2021)

Contextual Image Parsing via Panoptic Segment Sorting. - Jyh-Jing Hwang; Tsung-Wei Ke; Stella X. Yu (MULL @ ACM Multimedia, 2021)

Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformers. - Tsung-Wei Ke; Jyh-Jing Hwang; Yunhui Guo; Xudong Wang 007; Stella X. Yu (CVPR, 2022)

CAST: Concurrent Recognition and Segmentation with Adaptive Segment Tokens. - Tsung-Wei Ke; Stella X. Yu (CoRR, 2022)

Learning Visual Groupings and Representations with Minimal Human Labels - Tsung-Wei Ke (2022)

ChainedDiffuser: Unifying Trajectory Diffusion and Keypose Prediction for Robotic Manipulation. - Zhou Xian; Nikolaos Gkanatsios; Théophile Gervet; Tsung-Wei Ke; Katerina Fragkiadaki (CoRL, 2023)

Test-time Adaptation of Discriminative Models via Diffusion Generative Feedback. - Mihir Prabhudesai; Tsung-Wei Ke; Alexander C. Li; Deepak Pathak; Katerina Fragkiadaki (NeurIPS, 2023)

Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback. - Mihir Prabhudesai; Tsung-Wei Ke; Alexander C. Li; Deepak Pathak; Katerina Fragkiadaki (CoRR, 2023)

Local pseudo-attributes for long-tailed recognition. - Dong-Jin Kim 003; Tsung-Wei Ke; Stella X. Yu (Pattern Recognit. Lett., 2023)

3D Diffuser Actor: Policy Diffusion with 3D Scene Representations. - Tsung-Wei Ke; Nikolaos Gkanatsios; Katerina Fragkiadaki (CoRL, 2024)

Diffusion-ES: Gradient-Free Planning with Diffusion for Autonomous and Instruction-Guided Driving. - Brian Yang; Huangyuan Su; Nikolaos Gkanatsios; Tsung-Wei Ke; Ayush Jain; Jeff G. Schneider; Katerina Fragkiadaki (CVPR, 2024)

Learning Hierarchical Image Segmentation For Recognition and By Recognition. - Tsung-Wei Ke; Sangwoo Mo; Stella X. Yu (ICLR, 2024)

Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Following. - Brian Yang; Huangyuan Su; Nikolaos Gkanatsios; Tsung-Wei Ke; Ayush Jain; Jeff Schneider 001; Katerina Fragkiadaki (CoRR, 2024)

3D FlowMatch Actor: Unified 3D Policy for Single- and Dual-Arm Manipulation. - Nikolaos Gkanatsios; Jiahe Xu; Matthew Bronars; Arsalan Mousavian; Tsung-Wei Ke; Katerina Fragkiadaki (CoRR, 2025)