Papers › Agent Journey Beyond RGB: Unveiling Hybrid Semantic-Spatial Environmental...

Agent Journey Beyond RGB: Unveiling Hybrid Semantic-Spatial Environmental Representations for Vision-and-Language Navigation

9 Dec 2024arXiv:2412.06465archive 2025-07-28

Xuesong Zhang, Yunbo Xu, Jia Li, Zhenzhen Hu, Richnag Hong

Navigating unseen environments based on natural language instructions remains difficult for egocentric agents in Vision-and-Language Navigation (VLN). Existing approaches primarily rely on RGB images for environmental representation, underutilizing latent textual semantic and spatial cues and leaving the modality gap between instructions and scarce environmental representations unresolved. Intuitively, humans inherently ground semantic knowledge within spatial layouts during indoor navigation. Inspired by this, we propose a versatile Semantic Understanding and Spatial Awareness (SUSA) architecture to encourage agents to ground environment from diverse perspectives. SUSA includes a Textual Semantic Understanding (TSU) module, which narrows the modality gap between instructions and environments by generating and associating the descriptions of environmental landmarks in agent's immediate surroundings. Additionally, a Depth-enhanced Spatial Perception (DSP) module incrementally constructs a depth exploration map, enabling a more nuanced comprehension of environmental layouts. Experiments demonstrate that SUSA's hybrid semantic-spatial representations effectively enhance navigation performance, setting new state-of-the-art performance across three VLN benchmarks (REVERIE, R2R, and SOON). The source code will be publicly available.

Code

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Results from the paper archive 2025-07-28

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections