Baochang Zhang

54

Papers

74

Total Citations

Papers (54)

Controllable Mind Visual Diffusion Model

Tuning-Free Inversion-Enhanced Control for Consistent Image Editing

DiffuX2CT: Diffusion Learning to Reconstruct CT Images from Biplanar X-Rays

IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts

WaveMamba: Wavelet-Driven Mamba Fusion for RGB-Infrared Object Detection

Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization

UV-IDM: Identity-Conditioned Latent Diffusion Model for Face UV-Texture Generation

A General and Efficient Training for Transformer via Token Expansion

ZONE: Zero-Shot Instruction-Guided Local Editing

Learning 1-Bit Tiny Object Detector with Discriminative Feature Refinement

Sparse Representation Classification With Manifold Constraints Transfer

Self-Learning Scene-Specific Pedestrian Detectors Using a Progressive Latent Model

Cross-Modality Binary Code Learning via Fusion Similarity Hashing

Modulated Convolutional Networks

Circulant Binary Convolutional Networks: Enhancing the Performance of 1-Bit DCNNs With Circulant Back Propagation

Towards Optimal Structured CNN Pruning via Generative Adversarial Learning

Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression

Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks

HRank: Filter Pruning Using High-Rank Feature Map

Cogradient Descent for Bilinear Optimization

Toward Joint Thing-and-Stuff Mining for Weakly Supervised Panoptic Segmentation

Layer-Wise Searching for 1-Bit Detectors

Bi-Level Doubly Variational Learning for Energy-Based Latent Variable Models

IntraQ: Learning Synthetic Images With Intra-Class Heterogeneity for Zero-Shot Network Quantization

Q-DETR: An Efficient Low-Bit Quantized Detection Transformer

AttriCLIP: A Non-Incremental Learner for Incremental Knowledge Learning

Implicit Diffusion Models for Continuous Super-Resolution

Few-Shot Learning With Visual Distribution Calibration and Cross-Modal Distribution Alignment

Multinomial Distribution Learning for Effective Neural Architecture Search

Universal Adversarial Perturbation via Prior Driven Uncertainty Approximation

Bayesian Optimized 1-Bit CNNs

Aha! Adaptive History-Driven Attack for Decision-Based Black-Box Models

Parallel Detection-and-Segmentation Learning for Weakly Supervised Instance Segmentation

IDARTS: Interactive Differentiable Architecture Search

Representation Disparity-aware Distillation for 3D Object Detection

SET: Spectral Enhancement for Tiny Object Detection

Interpretable Neural Network Decoupling

NAS-Count: Counting-by-Density with Neural Architecture Search

PAMS: Quantized Super-Resolution via Parameterized Max Scale

IDa-Det: An Information Discrepancy-Aware Distillation for 1-Bit Detectors

Recurrent Bilinear Optimization for Binary Neural Networks

Anti-Retroactive Interference for Lifelong Learning

Anti-Bandit Neural Architecture Search for Model Defense

DFM: Differentiable Feature Matching for Anomaly Detection

Uncertainty-Aware Gradient Stabilization for Small Object Detection

Dynamic Clustering Convolutional Neural Network

Graph Structure Refinement with Energy-based Contrastive Learning

Bi-ViT: Pushing the Limit of Vision Transformer Quantization

Variational Structured Semantic Inference for Diverse Image Captioning

Rotated Binary Neural Network

Dual-stream Network for Visual Recognition

FNeVR: Neural Volume Rendering for Face Animation

Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

Q-DM: An Efficient Low-bit Quantized Diffusion Model