Search Results for author:
Found 8 papers, 1 papers with code
RoadFormer: Duplex Transformer for RGB-Normal Semantic Road Scene Parsing
Additionally, we release SYN-UDTIRI, the first large-scale road scene parsing dataset that contains over 10, 407 RGB images, dense depth images, and the corresponding pixel-level annotations for both freespace and road defects of different shapes and sizes.
Dive Deeper into Rectifying Homography for Stereo Camera Online Self-Calibration
Instead, we introduce four new evaluation metrics to quantify the robustness and accuracy of extrinsic parameter estimation, applicable to both single-pair and multi-pair cases.
SemanticCAP: Chromatin Accessibility Prediction Enhanced by Features Learning from a Language Model
Basically, we merge the features provided by the gene language model into our chromatin accessibility model.
TrajGen: Generating Realistic and Diverse Trajectories with Reactive and Feasible Agent Behaviors for Autonomous Driving
In particular, TrajGen consists of the multi-modal trajectory prediction stage and the reinforcement learning based trajectory modification stage.
Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs
Our method achieves the state-of-the-art performance on ImageNet, 80. 7% top-1 accuracy with 194M FLOPs.
Ranked #574 on
Image Classification
on ImageNet
Super-operator structures and no-go theorems for dissipative quantum phase transitions
In the thermodynamic limit, the steady states of open quantum many-body systems can undergo nonequilibrium phase transitions due to a competition between coherent and driven-dissipative dynamics.
Quantum Physics Quantum Gases
AutoBSS: An Efficient Algorithm for Block Stacking Style Search
Neural network architecture design mostly focuses on the new convolutional operator or special topological structure of network block, little attention is drawn to the configuration of stacking each block, called Block Stacking Style (BSS).
DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks
On one hand, we can reduce the computation cost remarkably while maintaining the performance.
