← Authors

Ziming Zhang

28 papers · 2011–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (14) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (46) πŸ† Keyword Champion πŸ† Grand Slam ⚑ Prolific Year (6) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (137) πŸ“ˆ Trend Setter πŸ’Ž Century Club (28) πŸ”₯ Unstoppable (6) ❓ The Questioner

Conferences

CVPR (8) ICCV (5) NIPS (5) WACV (5) ICLR (2) AAAI (1) ECCV (1) ICML (1)

Top co-authors

Venkatesh Saligrama (7) Xinming Huang (6) Fangzhou Lin (4) Yun Yue (4) Guanghui Wang (4) Yanhua Li (3) Yecheng Lyu (3) Yuting Chen (2) Xin Zhang (2) Kazunori Yamada (2)

Keywords

convolutional neural network (4) deep learning (3) representation learning (2) homography estimation (2) contrastive learning (2) point cloud (2) image alignment (2) 3d vision (2) bilevel optimization (2) deep neural network (2) gradient descent (2) point cloud completion (2) neural network optimization (2) chamfer distance (2) neural network training (1) feature learning (1) stochastic gradient descent (1) vision transformer (1) robust optimization (1) dimensionality reduction (1)

Papers

Active feature acquisition via explainability-driven ranking ICML 2025
GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching ICLR 2025
Understanding Hyperbolic Metric Learning Through Hard Negative Sampling WACV 2024
Learning Lightweight Neural Networks via Channel-Split Recurrent Convolution WACV 2023
PRISE: Demystifying Deep Lucas-Kanade With Strongly Star-Convex Constraints for Multimodel Image Alignment CVPR 2023
InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion NIPS 2023
Hyperbolic Chamfer Distance for Point Cloud Completion ICCV 2023
Robust Object Detection with Inaccurate Bounding Boxes ECCV 2022
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks With Implicit Gradients CVPR 2022
EllipsoidNet: Ellipsoid Representation for Point Cloud Classification and Segmentation WACV 2022
SBO-RNN: Reformulating Recurrent Neural Networks via Stochastic Bilevel Optimization NIPS 2021
Deep Lucas-Kanade Homography for Multimodal Image Alignment CVPR 2021
Self-Supervised Geometric Features Discovery via Interpretable Attention for Vehicle Re-Identification and Beyond ICCV 2021
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? ICLR 2020
Towards Learning Affine-Invariant Representations via Data-Efficient CNNs WACV 2020
Automatic Building and Labeling of HD Maps with Deep Learning AAAI 2020
Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters WACV 2020
f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning NIPS 2020
Learning to Segment 3D Point Clouds in 2D Image Space CVPR 2020
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning CVPR 2018
Attention-Based Multimodal Fusion for Video Description ICCV 2017
Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks NIPS 2017
Zero-Shot Learning via Joint Latent Similarity Embedding CVPR 2016
Efficient Training of Very Deep Neural Networks for Supervised Hashing CVPR 2016
Zero-Shot Learning via Semantic Similarity Embedding ICCV 2015
Group Membership Prediction ICCV 2015
BING: Binarized Normed Gradients for Objectness Estimation at 300fps CVPR 2014
Learning Anchor Planes for Classification NIPS 2011