Computer Vision ECCV 2024 Workshops: Milan, Italy, September 29October 4, 2024, Proceedings, Part XI [Pehme köide]

DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised
Vector LoRA of the Foundation Model.- LocalMamba: Visual State Space Model
with Windowed Selective Scan.- Compositional Text-to-Image Generation with
Feedforward Layout Generation.- PackMambaEfficient Processing of
Variable-Length Sequences in Mamba training.- Down-Sampling Inter-Layer
Adapter for Parameter and Computation Efficient Ultra-Fine-Grained Image
Recognition.- Memory-Efficient Vision Transformers: An Activation-Aware
Mixed-Rank Compression Strategy.- LLaMA-NAS: Efficient Neural Architecture
Search for Large Language Models.- Improving Hyperparameter Optimization with
Checkpointed Model Weights.- MagicDec: Breaking the Latency-Throughput
Tradeoff for Long Contexts with Speculative Decoding.- Mixed Non-linear
Quantization for Vision Transformers.- CycleBNN: Cyclic Precision Training in
Binary Neural Networks.- DailyMAE: Towards Pretraining Masked Autoencoders in
One Day.- EPTQ: Enhanced Post-Training Quantization via Hessian-guided
Network-wise Optimization.- Generalized SAM: Efficient Fine-Tuning of SAM for
Variable Input Image Sizes.- LightAvatar: Efficient Head Avatar as Dynamic
Neural Light Field.- Giving each task what it needs - leveraging structured
sparsity for tailored multi-task learning.- ERF-NAS: Efficient Receptive
Field-based Zero-Shot NAS for Object Detection.- CA3D:
Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on
the Edge.- Memory-Optimized Once-For-All network.- Famba-V: Fast Vision Mamba
with Cross-Layer Token Fusion.- Latent Distillation for Continual Object
Detection at the Edge.- MCUBench: A Benchmark of Tiny Object Detectors on
MCUs.- Optimizing Resource Consumption in Diffusion Models through
Hallucination Early Detection.