VisionLab Events
HIGHLIGHT
OTHER NEWS
ReViT: Enhancing vision transformers with residual attention
Vision Transformer (ViT) self-attention mechanism is characterized by feature collapse in deeper layers, resulting in the vanishing of low-level visual features. However, such features can
2 Settembre 2024 Nessun commento
S-GEAR: Semantically Guided Representation Learning for Action Anticipation (ECCV2024)
Action anticipation is forecasting future activity from a partially observed sequence of events. However, this task is exposed to intrinsic future uncertainty and the difficulty
2 Settembre 2024 Nessun commento
23 Agosto 2024 Nessun commento
23 Agosto 2024 Nessun commento
23 Agosto 2024 Nessun commento
23 Agosto 2024 Nessun commento
Computer Vision Conferences
- Overcoming Compute and Memory Bottlenecks with FlashAttention-4 on NVIDIA Blackwell
- Scaling NVFP4 Inference for FLUX.2 on NVIDIA Blackwell Data Center GPUs
- Streamlining CUB with a Single-Call API
- Multimodal reinforcement learning with agentic verifier for AI agents
- How to Train an AI Agent for Command-Line Tasks with Synthetic Data and Reinforcement Learning
- OptiMind: A small language model with optimization expertise
- How to Write High-Performance Matrix Multiply in NVIDIA CUDA Tile
- NVIDIA DLSS 4.5 Delivers Super Resolution Upgrades and New Dynamic Multi Frame Generation
- Learn How NVIDIA cuOpt Accelerates Mixed Integer Optimization using Primal Heuristics
- Reimagining LLM Memory: Using Context as Training Data Unlocks Models That Learn at Test-Time
- Multi-Agent Warehouse AI Command Layer Enables Operational Excellence and Supply Chain Intelligence
- Build an AI Catalog System That Delivers Localized, Interactive Product Experiences
- Building Generalist Humanoid Capabilities with NVIDIA Isaac GR00T N1.6 Using a Sim-to-Real Workflow
- Accelerating LLM and VLM Inference for Automotive and Robotics with NVIDIA TensorRT Edge-LLM
- Delivering Massive Performance Leaps for Mixture of Experts Inference on NVIDIA Blackwell
OpenCV News
- Overcoming Compute and Memory Bottlenecks with FlashAttention-4 on NVIDIA Blackwell
- Scaling NVFP4 Inference for FLUX.2 on NVIDIA Blackwell Data Center GPUs
- Streamlining CUB with a Single-Call API
- Multimodal reinforcement learning with agentic verifier for AI agents
- How to Train an AI Agent for Command-Line Tasks with Synthetic Data and Reinforcement Learning
- OptiMind: A small language model with optimization expertise
- How to Write High-Performance Matrix Multiply in NVIDIA CUDA Tile
- NVIDIA DLSS 4.5 Delivers Super Resolution Upgrades and New Dynamic Multi Frame Generation
- Learn How NVIDIA cuOpt Accelerates Mixed Integer Optimization using Primal Heuristics
- Reimagining LLM Memory: Using Context as Training Data Unlocks Models That Learn at Test-Time
- Multi-Agent Warehouse AI Command Layer Enables Operational Excellence and Supply Chain Intelligence
- Build an AI Catalog System That Delivers Localized, Interactive Product Experiences
- Building Generalist Humanoid Capabilities with NVIDIA Isaac GR00T N1.6 Using a Sim-to-Real Workflow
- Accelerating LLM and VLM Inference for Automotive and Robotics with NVIDIA TensorRT Edge-LLM
- Delivering Massive Performance Leaps for Mixture of Experts Inference on NVIDIA Blackwell
PyTorch News
- Overcoming Compute and Memory Bottlenecks with FlashAttention-4 on NVIDIA Blackwell
- Scaling NVFP4 Inference for FLUX.2 on NVIDIA Blackwell Data Center GPUs
- Streamlining CUB with a Single-Call API
- Multimodal reinforcement learning with agentic verifier for AI agents
- How to Train an AI Agent for Command-Line Tasks with Synthetic Data and Reinforcement Learning
- OptiMind: A small language model with optimization expertise
- How to Write High-Performance Matrix Multiply in NVIDIA CUDA Tile
- NVIDIA DLSS 4.5 Delivers Super Resolution Upgrades and New Dynamic Multi Frame Generation
- Learn How NVIDIA cuOpt Accelerates Mixed Integer Optimization using Primal Heuristics
- Reimagining LLM Memory: Using Context as Training Data Unlocks Models That Learn at Test-Time
- Multi-Agent Warehouse AI Command Layer Enables Operational Excellence and Supply Chain Intelligence
- Build an AI Catalog System That Delivers Localized, Interactive Product Experiences
- Building Generalist Humanoid Capabilities with NVIDIA Isaac GR00T N1.6 Using a Sim-to-Real Workflow
- Accelerating LLM and VLM Inference for Automotive and Robotics with NVIDIA TensorRT Edge-LLM
- Delivering Massive Performance Leaps for Mixture of Experts Inference on NVIDIA Blackwell
Nvidia Developers News
- Overcoming Compute and Memory Bottlenecks with FlashAttention-4 on NVIDIA Blackwell
- Scaling NVFP4 Inference for FLUX.2 on NVIDIA Blackwell Data Center GPUs
- Streamlining CUB with a Single-Call API
- Multimodal reinforcement learning with agentic verifier for AI agents
- How to Train an AI Agent for Command-Line Tasks with Synthetic Data and Reinforcement Learning
- OptiMind: A small language model with optimization expertise
- How to Write High-Performance Matrix Multiply in NVIDIA CUDA Tile
- NVIDIA DLSS 4.5 Delivers Super Resolution Upgrades and New Dynamic Multi Frame Generation
- Learn How NVIDIA cuOpt Accelerates Mixed Integer Optimization using Primal Heuristics
- Reimagining LLM Memory: Using Context as Training Data Unlocks Models That Learn at Test-Time
- Multi-Agent Warehouse AI Command Layer Enables Operational Excellence and Supply Chain Intelligence
- Build an AI Catalog System That Delivers Localized, Interactive Product Experiences
- Building Generalist Humanoid Capabilities with NVIDIA Isaac GR00T N1.6 Using a Sim-to-Real Workflow
- Accelerating LLM and VLM Inference for Automotive and Robotics with NVIDIA TensorRT Edge-LLM
- Delivering Massive Performance Leaps for Mixture of Experts Inference on NVIDIA Blackwell